Associate Director- AI Engineering

Key Responsibilites

AI Engineering & Technical Leadership

• Lead the architecture and end-to-end delivery of complex agen c AI, RAG, and LLM powered applica ons and products at Trinity, from solu on design through product on deployment.

• Act as the technical authority for agen c systems, defining reference architectures, engineering pa erns, evalua on approaches, and guardrails across Trinity.

• Enforce adherence to engineering standards: coding conven ons, tes ng requirements, CI/CD prac ces, security and RBAC pa erns, and agent harness implementa on — not as bureaucracy, but as the founda on that makes the team go faster over me.

• Guide teams on mul-agent architectures, MCP/A2A interoperability, agent memory, tool use, human-in-the-loop workflows, model selec on, inference opmisa on, and AI applica on observability.

• Stay hands-on with cri cal technical problems and prototypes across frameworks and plaorms such as LangGraph, AWS Bedrock, Snowflake Cortex, Azure AI Foundry, and Databricks.

• Partner with Data Science, Product, Cloud/IT, and client-facing teams to translate business requirements into shippable AI solu ons and deployment architectures.

• Track progress across parallel workstreams; surface blockers early, escalate when needed, and remove obstacles so engineers can focus on building rather than navigating process.

AI Platform & Deployment Accelera on

• Lead the AI Pla orm/Founda ons engineering team responsible for the infrastructure, tooling, reusable components, and developer experience that underpin AI delivery.

• Ensure AI workloads are produc on-ready by design, with standardised pa erns for containerisa on, CI/CD, model serving, orchestra on, observability, security, and environment management.

• Drive reusable pla orm capabili es, self-service deployment pa erns, and infrastructure automa on that reduce the me from AI prototype to produc on.

• Ensure infrastructure and pla orm configura ons meet compliance requirements relevant to Trinity's life sciences client base — data residency, access audit trails, and environment isolation on between workloads where required.

• Partner with enterprise IT/cloud teams where infrastructure is centrally governed, transla ng AI workload requirements into secure, scalable, and appropriately sized platform capabilities.

• Own pla orm reliability, security, cost opmisa on, and opera onal readiness across AI workloads, including cloud infrastructure, Kubernetes, networking, IAM/RBAC, secrets, and observability.

Team Growth, Mentorship & Culture

• Lead and develop AI Engineers and Pla orm Engineers, se ng a high technical bar through architecture reviews, design reviews, coaching, and hands-on technical leadership.

• Own delivery across mul ple AI engineering workstreams — managing priori es,

dependencies, technical risks, and resource constraints while ensuring predictable client delivery.

• Identify platform and engineering bo lenecks proac vely and drive improvements that increase team velocity, quality, and deployment reliability.

• Foster a culture of ownership, high standards, and con nuous improvement; be the kind of technical leader people want to work for and learn from.

• Partner closely with Data Scien sts, Product Managers, and business stakeholders to translate client needs into scalable AI solu ons and clear engineering roadmaps.

• Drive hiring, capability development, knowledge sharing, and adop on of AI-enabled engineering prac ces across various teams.

Stay Current & Drive Adopt on of What Works

• Stay ahead of the agen c AI field — evaluate new frameworks, protocols, and techniques with a critical eye and bring well-formed recommenda ons to the team on what is worth adoping.

• Champion the adop on of AI-enabled development prac ces that improve team productivity:

code generation, automated testing, documentation tooling, and developer experience improvements.

What We Are Looking For

• 12+ years of soware/technology engineering experience, with 5+ years in AI/ML, GenAI, or AI applica on engineering and demonstrated technical leadership of engineering teams.

• Deep exper se in LLM applica ons, RAG, agen c AI, and produc on AI engineering, with strong soware engineering fundamentals in Python, Spark & SQL.

• Proven experience designing and deploying enterprise AI solu ons across cloud pla orms such as AWS, Azure, Databricks, or Snowflake (AWS preferred).

• Strong understanding of AI pla orm engineering, including Docker/Kubernetes, CI/CD, infrastructure automa on, model serving, observability, security, and cloud architecture.

• Demonstrated ability to establish engineering standards and reusable pla orms that materially improve AI delivery speed, reliability, and scale.

• Strong stakeholder management and communica on skills, with the ability to influence senior technology and business leaders while remaining technically credible with engineers.

• Experience in life sciences, Pharma, or other regulated enterprise environments is a strong differentiator.

Degree in Computer Science, Engineering, or related field from IITs, NITs,

BITS, or comparable; strong applied track record considered equally.

Why This Role Matters

This role sits at the intersec on of AI engineering, pla orm engineering, and client delivery. The Associate Director will shape how Trinity builds and deploys AI at scale — ensuring that great AI ideas do not remain prototypes, but move rapidly through a secure, reusable, and produc on ready platform into solutions that create measurable value for clients. If you are energised by the combina on of deep technical work, team ownership, and genuine influence over how an AI

organisa on develops, we would like to meet you.