AI Infrastructure Lead Jobs

Our client, an AI-focused FinTech company, is hiring a Senior Backend Engineer to join their team in Manhattan, New York. The successful candidate will take the lead for core systems, from owning the overall architecture and building systems that are low-latency, resilient and cost-efficient.


Responsibilities

• Design, build and maintain backend services that are high-performance, resilient and easy to scale.

• Define service boundaries, data models and API contracts to enable independent team development.

• Set performance benchmarks and SLOs, designing systems for durability and graceful degradation under load.

• Lead technical design reviews and mentor engineers on best practices in code quality, testing, and operations.

• Take ownership of critical systems, including queue orchestration (Temporal), caching (Redis) and infrastructure automation.

Skillset

• Proven expertise building Node.js/TypeScript services.

• Experience with Go in production is a plus.

• Solid grasp of memory management, distributed systems, durable execution and edge computing.

• Hands-on experience with Temporal (or similar durable workflow systems) and Redis at scale.

• Comfortable deploying and operating services in modern cloud environments with strong observability practices.

• Familiarity with LLM integrations and their operational considerations is a plus.

• Strong communication and decision-making skills.

• Ability to make both high-level architecture and detailed code design decisions.

• Experience working with agentic or LLM-driven workflows is a bonus.

Benefits

• Salary: $150K–$200K

• Equity.

• Health, dental and vision insurance.

• 401k with 3% automatic contribution.

Our client, a leading IT Services organization, are hiring a ServiceNow Technical Consultant to join their team remotely in the U.S. The successful candidate will partner with clients to design, implement and optimize ServiceNow solutions, driving improved service delivery, operational efficiency and supporting mission-critical initiatives across the Federal and Healthcare sectors.


Responsibilities

• Design, configure and maintain ServiceNow CMDBs to support complex enterprise environments.

• Lead ServiceNow Discovery initiatives, including MID Server setup, credential management and automated discovery processes.

• Create and manage Service Mapping, Business Service models and dependency mapping to ensure accurate service representation.

• Maintain CMDB integrity through effective data modelling, CI class structuring and relationship management.

• Collaborate with cross-functional stakeholders to seamlessly integrate ServiceNow solutions with existing IT infrastructure and workflows.

• Implement ITIL best practices, with a focus on Configuration, Change and Incident Management processes.

Skillset

• US Citizenship is a must.

• Minimum of 5 years’ experience managing enterprise CMDBs, including at least 3 years working specifically with ServiceNow CMDB.

• Certified in ServiceNow CSM and CSA is required.

• Proficient in ServiceNow Discovery, including configuration of MID Servers and integration with underlying infrastructure components.

• Comprehensive understanding of networking, cloud computing, storage systems and data centre environments.

• Expertise in Service Mapping and CMDB data modelling, including CI class structures and relationship design.

• Strong knowledge of ITIL frameworks, particularly Configuration, Change, and Incident Management.

• Exceptional communication, analytical, and stakeholder engagement abilities, with a focus on delivering practical, business-driven solutions.

Benefits

• Salary: $130,000 - $180,000 DOE

• Remote working.

• Comprehensive Benefits Package.

Our client, a venture-backed AI SaaS startup, are hiring a Senior AI/ML Engineer to join their product team in New York. The successful candidate will have the opportunity to tackle greenfield challenges and build core systems from the ground up.


Responsibilities

• Take ownership of the AI stack,  including selecting models, vector stores and cloud infrastructure to build a secure, high-performance pipeline.

• Manage the full AI workflow, including data ingestion, cleaning, training, evaluation, deployment, monitoring and fine-tuning.

• Operationalize AI by implementing CI/CD for models and data, ensuring reproducible experiments, monitoring for drift and maintaining usage dashboards.

• Optimize systems for enterprise requirements, balancing latency, cost, data privacy and compliance-friendly logging.

• Collaborate closely with product and engineering leadership to prioritize and execute high-impact initiatives.

• Make pragmatic technical decisions in ambiguous environments, balancing technical elegance with business needs.

• Help shape the engineering culture, tooling and processes in a fast-growing, early-stage startup.

Skillset

• Over 7 years of professional experience, including 5 years developing clean, production-ready code for distributed, cloud-native systems.

• At least 2 years of hands-on experience deploying LLM pipelines in production, with strong knowledge of tokenization, context windows, sampling strategies and common failure modes.

• Proven track record in shipping generative AI or NLP products that meet real-world constraints such as latency, cost and data privacy.

• Deep expertise in LLM tuning and retrieval, including prompting, RAG, embeddings, fine-tuning and hallucination mitigation.

• Strong expertise of broader ML/data science experience, transforming raw data into robust models.

• Experience in ML Ops, including CI/CD for models, experiment tracking, and production monitoring.

• Strong product instincts, able to prototype quickly, iterate and collaborate closely with domain experts.

• Demonstrated technical leadership through setting engineering standards, writing clear documentation and mentoring team members.

• Proficiency with ML/LLM tools and libraries, with the ability to explain complex code and system behavior clearly.

Benefits

• Salary: $160k - $220k DOE.

• Equity.

Our client, a fast-growing AdTech organization, is hiring a Machine Learning Engineer/Tech Lead to join their team in California. The successful candidate will build and scale advanced systems for prediction, recommendation and generative AI, as well be responsible for solving complex, large-scale machine learning challenges and delivering cutting-edge solutions.


Responsibilities

• Design, train and deploy ML models and large-scale systems for prediction, recommendation and content generation.

• Tackle advanced use cases including CTR/CVR prediction, ranking, fraud detection and cutting-edge generative methods (LLMs, transformers, diffusion models).

• Develop scalable algorithms combining deep learning, regression and hybrid rule-based techniques.

• Diagnose and resolve performance bottlenecks across infrastructure, tools and pipelines.

• Rapidly prototype, experiment and iterate on models using massive, real-world datasets.

• Guide and mentor junior engineers, and lead small technical projects when required.

• Leverage distributed computing and GPU environments to optimize model training and deployment.

Skillset

• Master’s or Bachelor’s degree in Computer Science, Engineering, Applied Sciences, Mathematics or similar.

• At least four years of experience in software engineering or applied Machine Learning.

• Proven record of building and deploying large-scale ML systems in production.

• Experience driving technical direction, mentoring teams or leading cross-functional projects.

• Strong foundation in algorithms, data structures and ML fundamentals.

Benefits

• Competitive compensation.

• Comprehensive benefits package.

Our client, a growing AI-driven startup, is hiring a a Staff Platform Engineer to join the team in California. The successful candidate will design and scale their core infrastructure, driving projects that improve system reliability, boost developer efficiency and elevate operational standards within their talented engineering team.


Responsibilities

• Design and build scalable backend systems that support complex data labeling workflows, enable real-time collaboration, and incorporate large language model (LLM) capabilities.

• Lead infrastructure initiatives focused on deployment, observability and performance optimization within a cloud-native environment.

• Develop secure, modular APIs and services that seamlessly integrate with both internal tools and customer-facing applications.

• Work closely with engineers, product managers and data operations teams to advance the company’s platform features and capabilities.

• Establish and maintain observability best practices - including logging, metrics, tracing and health monitoring - to deliver an exceptional developer experience.

• Guide architectural decisions involving service decomposition, asynchronous processing, scaling strategies and high-availability systems.

• Take ownership of the reliability and performance of critical services, including distributed task routing, model integrations and data pipelines.

• Mentor engineering team members in creating scalable, maintainable systems using contemporary engineering best practices.

Skillset

• Minimum of 8 years’ experience in backend or platform engineering, preferably within fast-growing SaaS or AI infrastructure companies.

• Proficient in Python programming, with hands-on experience using frameworks such as FastAPI.

• Strong expertise in cloud platforms (AWS, GCP or Azure), including container orchestration technologies like Docker and Kubernetes, and Infrastructure as Code tools such as Terraform.

• Experienced with SQL databases (e.g. PostgreSQL) and event-driven messaging systems (e.g. Kafka, RabbitMQ, Redis Streams).

• Well-versed in CI/CD pipelines, automated testing and deployment methodologies for large-scale production environments.

• Demonstrated ability to troubleshoot complex distributed systems, identify performance bottlenecks and build robust, resilient architectures.

• Comfortable working in early-stage, dynamic environments, taking initiative to identify and solve high-impact challenges.

• Experience integrating large language models (LLMs), working with ML/AI infrastructure or contributing to data labeling platforms is a plus.

• Design and build scalable, maintainable platform systems from the ground up.
• Develop robust backend services and APIs mainly with Python and using Rust for performance-critical components.
• Work closely with frontend teams on integrations using JavaScript and TypeScript.
• Automate infrastructure deployment using modern DevOps tools and Infrastructure as Code practices.
• Provide technical leadership by establishing best practices and guiding architectural decisions.
• Own features end-to-end, from initial concept through to production release.

• Proven experience in software development, with strong Python backend skills.
• Demonstrated success building systems from the ground up in fast-paced environments.
• Proficiency in JavaScript/TypeScript and modern frontend frameworks.
• Experience with Rust, or a willingness to learn it for performance-critical tasks.
• Hands-on familiarity with cloud platforms such as AWS, GCP or Azure.
• Experience with containerization using Docker and orchestration with Kubernetes.
• Strong system design skills, including designing clean APIs and scalable architectures.
• A DevOps mindset, with expertise in CI/CD pipelines, monitoring and observability.
• Excellent communication and teamwork skills.
• Passion for open-source and active contribution to community-driven projects.

• Salary: $100K - $220K DOE.
• Equity.
• Comprehensive health, dental and vision insurance.

• Architect, maintain and scale high-performance computing (HPC) and storage solutions across both on-premises and cloud environments.
• Collaborate with global teams to diagnose and resolve infrastructure challenges across operating systems, storage and networking.
• Champion innovation by exploring and implementing emerging technologies to enhance research infrastructure.
• Oversee and optimise a range of compute resources, including CPUs, GPUs and other specialised processing units.
• Work closely with software engineers to deliver seamless, high-performance platforms that power advanced research initiatives.

• Minimum of 5 years of experience in data engineering.
• Strong, hands-on experience with Databricks, especially in a production environment
• Solid expertise in Linux-based systems and environments.
• Hands-on experience with Infrastructure as Code tools, such as Ansible and Terraform.
• Working knowledge of cloud platforms like AWS, GCP or Azure.
• Genuine interest in high-performance computing and solving complex system-level challenges.
• Proven ability to diagnose and resolve issues across various layers of infrastructure.
• Effective communicator and team player, comfortable working in cross-functional and globally distributed teams.

• Salary: $250k - $300k.
• Performance Bonus.
• 401(k) matching up to 50%.
• Health, dental, vision, mental health, disability and life insurance.