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Our client, an AI-driven legal tech company, is hiring a Founding Software Engineer to join the team in San Francisco, CA. The successful candidate will own the development and scaling of full-stack applications across the platform, combining product engineering, infrastructure and applied AI to deliver high-quality customer experiences.
Responsibilities-
Design, build and maintain production-grade full-stack applications using React and TypeScript.
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Develop scalable APIs, data models and backend services that support a rapidly evolving product.
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Design flexible and scalable data architectures using NoSQL databases.
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Build and maintain integrations with third-party APIs, authentication, payments and document platforms.
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Take end-to-end ownership of features, from initial design and development through deployment and continuous improvement.
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Leverage AI coding tools and agent-driven development workflows to accelerate engineering and improve productivity.
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Collaborate closely with product and design to turn customer needs into intuitive, high-quality product experiences.
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Continuously improve the platform's performance, reliability, scalability and developer experience.
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Contribute to technical architecture and engineering decisions as the platform and team scale.
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Solve complex and ambiguous technical problems within a fast-moving, highly iterative startup environment.
Skillset-
At least 2 years of professional software engineering experience, with a track record of building and shipping production-grade web applications.
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Strong proficiency in TypeScript, React and modern full-stack development.
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Hands-on experience designing, building and integrating APIs and backend services.
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Solid understanding of distributed systems, application architecture and scalable software design.
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Experience working with NoSQL databases and flexible data-modelling patterns.
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Comfortable using AI-assisted development tools, coding copilots and agent-based engineering workflows.
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Proven ability to own features end-to-end, from technical design and implementation through to production.
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Ability to work independently, navigate ambiguous requirements and make pragmatic technical decisions.
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Strong product mindset with a focus on shipping high-quality software that delivers meaningful customer value.
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Previous experience within an early-stage startup or other fast-paced engineering environment would be a big plus.
Benefits-
Salary: $120k - $180k
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Equity.
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Our client, a fast-growing AI FinTech company, is hiring a Staff-Level Software Engineer to join their team in New York. The successful candidate will take ownership of the foundational platform systems powering the company's AI products, building shared infrastructure that enables engineering teams to develop and deploy reliable, scalable AI solutions.
Responsibilities-
Design and develop the core AI agent platform, building shared frameworks for context management, verification, guardrails, evaluation, observability and developer tooling.
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Architect the financial context layer that enables AI agents to reason across ledger data, accounting policies, contracts, historical decisions, dimensions and permissions.
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Define and implement standards for AI reliability, auditability, verification and evaluation, ensuring AI-generated outputs can be trusted within critical financial workflows.
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Build scalable financial data infrastructure for ingesting, normalizing, reconciling and modeling data from ERPs, banks, billing, payroll, CRM and other enterprise systems.
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Design reliable orchestration systems capable of supporting complex, long-running and stateful AI workflows.
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Develop secure and fully traceable mechanisms for writing AI-generated actions back to ERPs and financial systems of record.
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Identify architectural bottlenecks and create reusable platforms, frameworks and abstractions that improve engineering productivity across the organization.
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Lead key architectural decisions across distributed systems, AI infrastructure, data platforms, enterprise integrations and product architecture.
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Collaborate directly with accountants, controllers, CFOs and customers to understand complex financial processes and translate them into scalable production systems.
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Remain deeply hands-on, using modern AI development and coding tools to design, build, test and ship production-grade systems.
Skillset-
At least 8 years of professional software engineering experience, including experience operating at Staff, Principal or equivalent senior IC level.
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Deep expertise in backend engineering and distributed systems, including areas such as data infrastructure, workflow engines, transactional systems, integration platforms or AI agent platforms.
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Strong programming skills in Python, Go, Java, Rust or a comparable modern language, with the ability to quickly become productive in Python.
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Proven experience designing platform infrastructure, frameworks and architectural abstractions that support multiple engineering teams and products.
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Track record of leading significant technical and architectural decisions, particularly within ambiguous, rapidly evolving environments.
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Strong understanding of system reliability, scalability, observability, data integrity, security and production infrastructure.
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Ability to quickly understand complex business domains and translate workflows and requirements into scalable, reusable technical solutions.
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A high-ownership approach, with the ability to identify problems, define solutions, make technical decisions and deliver with minimal direction.
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Experience working within an early-stage technology company, ideally from pre-seed through Series B.
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Comfortable remaining deeply hands-on across AI systems, backend engineering, infrastructure, data platforms and product development.
Benefits-
Salary: $200k - $250k DOE.
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Equity:
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Comprehensive medical, dental and vision insurance.
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401(k) match.
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Our client, a global AI and data-driven organization, are hiring a Developer Experience and Engineering Operations Lead to join their growing team in Dublin, Ireland. The successful candidate will help improve how engineering teams work by making software delivery faster, more consistent and less complex across global function by removing friction across the delivery lifecycle and enabling secure, high-quality and scalable software delivery at pace.
Responsibilities-
Own and deliver the Developer Experience and Engineering Operations roadmap, improving how engineers build, test, release and operate software.
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Identify and address friction points across the software development life-cycle using data, feedback and engineering insight.
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Design and implement pragmatic engineering standards, golden paths, reusable templates and delivery playbooks.
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Drive responsible adoption of AI-assisted development, including coding assistants and workflow automation.
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Define clear guardrails for AI usage, including prompt patterns, quality expectations and security boundaries.
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Promote adoption of internal AI platform capabilities, enabling governed reuse of AI-enabled solutions.
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Improve engineering operations across onboarding, documentation, knowledge sharing and operating cadences.
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Enhance CI/CD pipelines, observability, environment management, release processes and delivery transparency.
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Partner with Architecture, Platform, Cloud, Security and Product Engineering teams to improve end-to-end delivery capability.
Skillset-
Strong background in software engineering, DevOps, SRE, platform engineering or engineering operations.
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Proven track record of improving developer productivity across multiple teams or large organisations.
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Deep understanding of modern SDLC practices, including cloud-native development, CI/CD, APIs, observability and automation.
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Experience defining engineering standards, golden paths or reusable playbooks.
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Familiarity with modern engineering toolchains such as GitHub/GitLab, CI/CD platforms, IaC, containers, developer portals and AI tools.
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Strong stakeholder management and influence across engineering, architecture, security and product teams.
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Experience working with globally distributed engineering teams.
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Hands-on experience with AI-assisted development, including LLMs, prompt engineering and agentic workflows is a plus.
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Cloud platform experience with AWS, Azure or GCP is an advantage.
Benefits-
Salary: €112k - €128k.
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Bonus structure.
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Private healthcare, life assurance and income protection.
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Strong pension scheme.
** Please Note** Candidates must already be eligible to work in the Republic of Ireland. -
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Our client, a growing Digital Transformation Consulting organisation, is hiring a hands-on Senior Applied AI Engineer to join the team in Dublin, Ireland on a contract basis. The successful candidate will design, build and scale advanced Generative and Agentic AI systems, contributing to the development of production-ready agent workflows, sophisticated retrieval pipelines, robust evaluation frameworks and scalable backend services.
Responsibilities-
Design, build and operate end-to-end production-grade AI agent systems.
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Develop stateful agent workflows with checkpointing, retries and human-in-the-loop controls.
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Architect intelligent agents with planning, tool use, memory and escalation strategies.
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Implement advanced retrieval pipelines, including hybrid search, reranking and context construction.
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Build robust evaluation frameworks with datasets, regression testing and clear success metrics.
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Establish LLMOps / AgentOps practices, including observability across cost, latency, drift and failures.
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Optimise system performance across latency, cost and output quality (e.g. routing, caching, model selection).
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Develop scalable backend services using Python (e.g. FastAPI) and modern architectures.
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Deploy and maintain systems using Docker, Kubernetes and CI/CD pipelines.
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Translate business requirements into scalable, production-ready AI solutions.
Skillset-
Minimum of 4 years of experience in software engineering, applied machine learning or applied AI.
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Strong Python skills, with a solid grounding in modern engineering practices e.g. testing, code quality, version control.
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Demonstrated experience developing and deploying LLM-powered applications, including prompt design, evaluation and productionisation .
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Practical experience with agent frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI or Langfuse.
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Hands-on experience with retrieval systems and vector databases (e.g. Milvus, Pinecone, Weaviate, Chroma, FAISS).
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Good understanding of AI architecture patterns, including microservices, event-driven systems and multi-agent frameworks.
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Experience deploying applications on AWS, Azure or GCP using containerisation and CI/CD pipelines .
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Strong production mindset, with experience in monitoring, testing, governance and LLMOps practices.
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Exposure to developer copilots and rapid prototyping tools (e.g. Cursor, Windsurf, Replit, GitHub Copilot, Claude Code) is a plus.
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