Lead Consultant - Bespoke Engineering & AI Innovation

Posted 6 Days Ago
Be an Early Applicant
Chennai, Tamil Nadu, IND
In-Office
Expert/Leader
Biotech • Pharmaceutical • Manufacturing
The Role
Lead architecture and delivery of AI-first, cloud-native enterprise solutions. Define engineering patterns for Python and React, integrate LLMs and Agentic workflows, implement RAG/semantic retrieval with vector DBs, enforce AI governance/observability, optimize AI FinOps, mentor engineers, and partner with product and business teams to scale secure, compliant AI solutions for pharmaceutical use.
Summary Generated by Built In

Introduction to role:

Are you ready to architect AI-first systems that accelerate the discovery and delivery of life-changing medicines?

You will guide the end-to-end technical evolution of a high-impact portfolio of custom enterprise solutions. This strategic role integrates traditional engineering rigor with pioneering Agentic AI capabilities to drive innovation. The Lead is accountable for engineering quality, solution scalability, and delivery throughput, providing hands-on leadership across full-stack technologies and cloud-native AI architectures. Serving as the primary architect of the AI-augmented SDLC, the incumbent establishes formal standards while shaping the future of "Intelligent Bespoke" applications in close partnership with product and delivery teams. If you enjoy turning enterprise data into actionable knowledge and measurable business value, this role is for you!

Accountabilities:

  • Architectural Leadership & AI Strategy: Define and uphold engineering patterns for Python, React, and cloud services. Lead the move from traditional logic to Agentic workflows, ensuring custom solutions are "AI-first" by design.

  • AI-Augmented SDLC: Drive the integration of AI throughout the software lifecycle. Implement Model Context Protocol (MCP) to bridge the gap between local development environments and LLM-based assistants.

  • Engineering Quality & Governance: Reinstate structured code reviews with a focus on AI Governance. Establish quality gates that cover not just security and performance, but also LLM observability, hallucination mitigation, and bias detection.

  • Agentic Productivity: Mentor and upskill junior engineers on Agentic AI tools (GitHub Copilot, Cursor, Agent Builder). Shift the team’s focus from manual boilerplate to high-level system design.

  • FinOps for AI: Optimize cloud architectures for cost-efficiency. Lead AI FinOps by balancing token usage, model selection (SMMs vs. LLMs), and inference costs against business outcomes.

  • Solution Shaping & RAG Patterns: Partner with Business partners to scope work using RAG (Retrieval-Augmented Generation) and semantic search patterns to unlock value from enterprise data.

Essential Skills and Experience:

  • Experience: 10+ years in software engineering; 5+ years in a Technical Lead role.

  • Core Stack: Python (FastAPI, Flask, or Django) and React (TypeScript).

  • AI Specialization: Hands‑on LLM integration, prompt engineering, and orchestration frameworks (e.g., LangChain, AutoGen, or LlamaIndex).

  • Data Architecture: Strong SQL/NoSQL skills, plus experience with Vector Databases (e.g., Pinecone, Weaviate, or Milvus) for semantic retrieval.

  • Cloud & Infra: Expert-level Azure or AWS experience. Proficiency in IaC (Terraform/Bicep) and building AI-ready CI/CD pipelines.

  • Integration: Expertise in REST, event-driven architectures, and emerging protocols like (MCP).

Desirable Skills:

  • Enterprise Platforms: Experience integrating AI agents with Workday (HCM) or Power Platform.

  • AI Governance: Familiarity with compliance-aware development in regulated environments (e.g., Pharmaceutical or Finance), focusing on data privacy in AI models.

  • Containerization: Mastery of Docker and Kubernetes for deploying scalable AI microservices.

  • DevSecOps: Advanced understanding of secrets management and "Security for AI" (OWASP Top 10 for LLMs).

Why AstraZeneca:

This is a pivotal moment to join our technology transformation. We combine scientific ambition with leading digital platforms to turn complex data into decisions that change patient outcomes. You will work in an environment where unexpected teams collaborate to unleash bold thinking—where experimentation is encouraged, standards are high, and learning runs through the entire community. With investment and support behind you, you will scale AI safely and sustainably, building systems that matter. We value kindness alongside ambition, and we give you the autonomy to take ownership and run with ideas that move the enterprise forward.

Step into the lead and shape AI-first engineering with real-world impact—send your CV to start the conversation and help build the next chapter at AstraZeneca!

Date Posted

09-Jun-2026

Closing Date

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

Skills Required

  • 10+ years in software engineering
  • 5+ years in a Technical Lead role
  • Python (FastAPI, Flask, or Django)
  • React (TypeScript)
  • LLM integration, prompt engineering, and orchestration frameworks (LangChain, AutoGen, LlamaIndex)
  • SQL and NoSQL experience
  • Vector Databases (Pinecone, Weaviate, or Milvus) for semantic retrieval
  • Expert-level Azure or AWS experience
  • Infrastructure as Code (Terraform or Bicep)
  • Building AI-ready CI/CD pipelines
  • Integration expertise: REST, event-driven architectures, and Model Context Protocol (MCP)
  • Experience integrating AI agents with enterprise platforms (Workday HCM or Power Platform)
  • Familiarity with AI governance and compliance-aware development in regulated environments (pharmaceutical or finance)
  • Containerization and orchestration: Docker and Kubernetes
  • DevSecOps: secrets management and Security for AI (OWASP Top 10 for LLMs)
  • Experience with AI FinOps (token/cost optimization, model selection tradeoffs)
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The Company
90,000 Employees
Year Founded: 1999

What We Do

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company committed to excellence in the research, development, and commercialization of prescription medicines. With approximately 90,000 employees across 85 countries, the company aims to unlock the power of science to deliver innovative medicines that transform patient outcomes and improve healthcare for people, society, and the planet worldwide.

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