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Portfolio Product Lead, AI
Contract | Initial 9 months | Fully remote [country/EU]
A large healthcare enterprise is hiring a Portfolio Product Lead to decide where its AI and GenAI investment goes, and to make sure the initiatives it backs reach adoption and deliver measurable results.
You'll own the AI portfolio roadmap: setting priorities, challenging proposals, and guiding ideas from experimentation through to scaled delivery. You won't build the solutions yourself, but you'll need enough technical depth to work credibly with engineering, data and AI teams and to know when an approach is ready to scale or should be stopped.
What you'll do
- Own the AI portfolio roadmap, balancing business value, technical feasibility, risk and delivery capacity
- Work with business teams to identify where AI can improve processes, products or ways of working
- Turn opportunities into clear use cases, priorities and measurable success criteria
- Guide initiatives from discovery and experimentation through to implementation, adoption and ongoing evaluation
- Partner with engineering, data and AI teams to assess approaches, challenge assumptions and unblock delivery
- Align senior stakeholders on priorities, investment decisions and expected outcomes
- Manage dependencies and risks across the portfolio, adjusting direction as evidence emerges
- Build governance, security and human oversight into every initiative from the start
- Track adoption and business impact, and use the results to decide what to improve, scale or stop
What you'll bring
- Experience leading products, portfolios or transformation programmes in a complex organisation
- A track record of delivering AI or GenAI initiatives into real use, with concrete examples of implementation, adoption and results
- Current, practical exposure to AI tools and solutions, backed by a hands-on or previously hands-on technical background
- The ability to discuss AI capabilities, data requirements, evaluation, integration and limitations with technical teams
- Strong prioritisation skills and confidence making trade-offs between competing initiatives
- Excellent stakeholder management, including influencing senior leaders and bringing business and technology teams together
- A clear approach to measuring value, from setting a baseline to assessing outcomes
- Understanding of responsible AI, governance and the challenges of introducing AI into established enterprise systems
Nice to have
- Experience applying AI to software delivery, application modernisation or internal workflows
Interested? Send your CV to kylec@alldus.com or message me for a quick conversation about the role and contract.
Senior AI/ML Production Engineer (Python & MLOps)
Location: Remote (EU)
Contract: 12 months | Daily Rate Contract
Industry: Life Sciences / Clinical Research
Our client, a global life sciences organisation headquartered in Dublin, Ireland, is seeking an experienced Senior AI/ML Production Engineer to join their growing technology team on an initial 12-month contract.
This is a hands-on engineering role focused on taking AI and machine learning models developed by Data Science teams and transforming them into scalable, reliable, production-ready solutions.
Working closely with Data Scientists, Software Engineers and Cloud Architects, you will play a key role in bridging the gap between experimental models and enterprise production environments, supporting AI-driven applications and data processing within clinical research.
Key Responsibilities
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Productionise AI/ML Models: Take Python-based prototypes, algorithms and machine learning models from research environments and develop them into robust, scalable production services.
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Software Engineering: Design, develop and optimise Python applications, REST APIs, microservices and automated data pipelines to support AI/ML workloads.
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MLOps & Automation: Build and maintain CI/CD and MLOps pipelines covering automated testing, model deployment, versioning, monitoring and reproducibility.
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Performance Optimisation: Refactor and optimise existing Python code to improve execution speed, memory efficiency, reliability and scalability when processing large, complex datasets.
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Cloud & Infrastructure: Deploy and integrate AI/ML solutions within AWS and/or Azure environments, leveraging containerisation and orchestration technologies.
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Monitoring & Reliability: Implement production monitoring, logging, telemetry and model performance tracking to identify issues and maintain system reliability.
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Cross-functional Collaboration: Work closely with Data Science, Engineering and Cloud teams to translate experimental solutions into maintainable, production-grade applications.
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Security & Compliance: Apply secure engineering practices and support relevant data privacy and regulatory requirements within clinical and life sciences environments.
Skills & Experience
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5+ years of professional software engineering experience, including significant hands-on experience deploying and supporting AI/ML solutions in production.
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Strong Python engineering expertise, including writing clean, maintainable, well-tested and performance-optimised code.
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Proven experience taking machine learning models or Python-based analytical applications from prototype through to production deployment.
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Experience developing REST APIs, microservices and backend applications using frameworks such as FastAPI or Flask.
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Hands-on experience with MLOps, CI/CD and automated deployment, using tools such as MLflow, Databricks, Kubeflow, Airflow, DVC or similar.
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Strong experience with AWS and/or Azure, including Docker, Kubernetes and cloud-native deployment practices.
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Good understanding of machine learning workflows, model lifecycle management, monitoring and production troubleshooting.
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Experience working with SQL databases, data pipelines and large-scale data processing environments.
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Familiarity with modern software engineering practices, including Git, automated testing, code reviews and infrastructure automation.
Desirable Experience
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Experience working with PyTorch, TensorFlow, scikit-learn or other machine learning frameworks.
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Exposure to distributed processing technologies such as Apache Spark or Databricks.
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Experience optimising computationally intensive Python workloads or large-scale data pipelines.
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Familiarity with model monitoring, data drift detection and ML observability.
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Previous experience within life sciences, pharmaceuticals, clinical research, healthcare or other regulated environments.
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Understanding of GDPR, GxP or other relevant data governance and compliance requirements.
The Opportunity
This is an opportunity to work on real-world AI/ML applications within a global life sciences environment, helping bridge the gap between Data Science innovation and production engineering.
The successful candidate will have a strong software engineering background, practical experience deploying machine learning solutions and the ability to take ownership of the technical challenges involved in making AI systems scalable, reliable and production-ready.
Interested? Apply or get in touch to discuss the role, contract details and technical environment.
Our client, a growing fintech company, is hiring a Forward Deployed Engineer to join their team in New York City. The successful candidate will collaborate with finance, credit risk, servicing, collections and operations teams to automate manual processes using AI, while partnering with Product and Engineering to build AI solutions for merchants and partners.
Responsibilities
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Collaborate with business teams to understand their processes, identify improvements and define measurable outcomes.
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Lead projects from initial discovery and technical design through development, deployment and adoption.
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Develop reliable automations, data pipelines and AI agents that address business needs.
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Build evaluations to verify outputs before deployment and maintain accuracy as models, data and workflows evolve.
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Set up monitoring, exception handling and alerts with clear responsibilities and escalation procedures.
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Establish human review requirements, access controls, activity logging and boundaries for automated decisions.
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Work with Product and Engineering to develop customer-facing AI solutions that meet review and deployment standards.
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Develop reusable components, evaluation frameworks and deployment approaches to improve future delivery.
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Assess business results and present findings to senior leadership, including time savings, review and maintenance effort, and control effectiveness.
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Work closely with engineers in New York and India, using insights from deployments to shape the platform roadmap.
Skillset
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At least 3 years of experience in software engineering or technical deployment, including working directly with business users.
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Strong Python and SQL skills, with experience developing and maintaining production systems.
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Hands-on experience deploying LLM applications, including prompt engineering, AI agents and evaluation.
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Experience working with governed data in platforms, such as Databricks or ClickHouse.
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Ability to build reliable data pipelines, validate outputs and troubleshoot data quality issues.
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Strong discovery skills, with the ability to turn business workflows into clear technical requirements.
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Clear communication skills and confidence explaining technical decisions to nontechnical stakeholders.
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Ability to own delivery, navigate unclear requirements and identify valuable opportunities for automation.
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Experience in fintech, lending, payments, banking or another regulated environment is an advantage.
Benefits
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Salary: $145k - $195k.
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Equity.
Our client, an AI-driven healthcare organization, is hiring a Senior Backend Engineer to join the team in New York. The successful candidate will build and scale the infrastructure powering a real-time clinical monitoring platform, developing services that process high volumes of neurological data, support clinical workflows and deploy machine learning models into production.
Responsibilities
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Build and maintain Python and Go services to process and deliver real-time neurological data.
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Develop and optimise data models, ingestion pipelines and retention policies for high-frequency time-series data.
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Create and enhance APIs that underpin clinical workflows.
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Work alongside ML engineers to bring research models into production and ensure inference services run reliably.
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Strengthen platform performance and reliability through monitoring, alerting, capacity planning and incident reviews.
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Build software that meets regulated medical device standards, covering cybersecurity, traceability and change control.
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Own technical delivery from defining requirements through development, deployment and ongoing support.
Skillset
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At least 5 years' experience building and operating backend systems in production.
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Strong Python development skills, including testing and concurrency using threads, processes and asyncio.
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Hands-on experience with event-driven or stream-processing systems, including partitioning, checkpointing, backpressure and at-least-once delivery.
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Experience with containerisation and orchestration, preferably Kubernetes.
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Strong relational database skills, including schema design and query optimisation.
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A proactive, resourceful approach, with the ability to turn ambiguous requirements into reliable, monitored services.
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Clear communication skills, including the ability to explain technical decisions verbally and in writing.
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Experience with Go for networked or low-latency services and Azure services such as Event Hubs, Service Bus, Web PubSub, Blob Storage or AKS is a plus.
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Knowledge of large-scale data engineering, columnar formats such as Apache Arrow or Parquet, video processing or sub-second latency systems would be beneficial.
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Experience serving PyTorch models or developing healthcare technology and other regulated software would be an advantage.
Benefits
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Salary: $250k - $300k
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Equity.
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Comprehensive medical, dental and vision coverage.
Our client, a growing Healthtech organization, is hiring a Founding Principal Engineer to join their team in New York City. The successful candidate will lead the company's next phase of technical development, from shaping the technical strategy, building critical platform capabilities and guiding a distributed engineering team.
Responsibilities
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Shape the technical roadmap and architecture for telehealth services, electronic health records, clinician onboarding and patient-facing applications.
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Develop production software and tackle the platform's most demanding technical challenges.
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Assess whether to build solutions internally, purchase existing products or engage external partners.
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Lead and mentor offshore engineers, setting clear priorities and ensuring consistent delivery.
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Introduce engineering standards for code reviews, testing, deployments, on-call support and incident management.
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Ensure platform reliability and data security, with engineering practices that support HIPAA compliance and payer requirements.
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Drive practical AI adoption across clinical, operational and engineering processes.
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Develop and refine the technology stack, currently using TypeScript, Node.js, React and AWS.
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Collaborate with clinical, growth and operations teams to turn business requirements into clear technical delivery plans.
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Hire and onboard US-based engineers, shaping the team's structure, working practices and culture as the company grows.
Skillset
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At least 8 years' experience developing production software, including time in a Staff or Principal Engineer role.
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Strong full-stack engineering skills, covering database design, backend services and user interfaces.
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Proven ability to define architecture and deliver complex systems from initial design through to production.
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Experience leading engineering teams while remaining hands-on with development.
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A track record of raising engineering standards, mentoring developers and improving software quality.
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Experience working effectively with distributed or offshore engineering teams.
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Experience building software in regulated environments or systems with demanding reliability and data protection requirements.
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Sound technical judgement around security, reliability and data integrity, with healthcare experience an advantage.
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Ability to navigate ambiguity, manage competing priorities and deliver within a growing organisation.
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Strong communication skills, with confidence engaging senior leaders and explaining technical decisions to non-technical stakeholders.
Benefits
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Salary: $200k - $240k.
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Equity.
Our client, an IT services provider supporting US federal government agencies, is hiring a ServiceNow Developer with active Secret clearance for a contract role in Maryland. The successful candidate will build custom applications, integrations and automated workflows across SPM, ITSM, ITOM and CMDB, delivering secure, reliable solutions that meet performance standards and federal security requirements.
Responsibilities
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Build and deploy ServiceNow solutions, scoped applications and integrations in line with established development standards.
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Turn business requirements, user stories and wireframes into practical technical solutions.
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Develop workflows, Business Rules, UI Policies and automated processes using Flow Designer and IntegrationHub.
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Review code, contribute to development standards and embed secure coding practices.
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Diagnose and resolve platform issues to maintain reliability and optimise performance.
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Deliver platform upgrades, apply patches and support new module rollouts.
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Create technical documentation and provide stakeholders with training and ongoing guidance.
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Maintain compliance with RMF, FedRAMP and relevant federal security frameworks, supporting software accreditation processes.
Skillset
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Active Secret clearance is essential.
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Minimum of 5 years' ServiceNow development experience, with progressively greater responsibility.
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A current ServiceNow Certified Application Developer (CAD) and/or Certified System Administrator (CSA) certification.
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CIS-ITSM and/or CIS-SPM certifications would be a plus.
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Strong technical skills in JavaScript, Glide APIs and ServiceNow Studio.
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Practical experience with ITSM, ITOM, CMDB, Flow Designer and IntegrationHub.
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Experience delivering projects within Agile/Scrum teams.
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Demonstrated experience supporting the Risk Management Framework (RMF) and federal software accreditation processes.
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Strong communication and teamwork skills, with the ability to explain technical solutions clearly to colleagues, senior stakeholders and customers.