AstraZeneca

Healthcare

LeadConsultant-BespokeEngineering&AI

₹35–55L ~AI est. India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Lead Consultant - Bespoke Engineering & AI at AstraZeneca. Skills: AI-first systems, Agentic AI, Cloud-native AI architectures, AI-augmented SDLC. Architect AI-first systems. Guide technical evolution”

What You'll Achieve.

Accelerate discovery of medicines; Accelerate delivery of medicines; Turn enterprise data into knowledge; Turn enterprise data into business value; Scale AI safely; Scale AI sustainably; Build systems that matter

Industry & Context.

Healthcare
Problems you'll solve

Root cause analysis; Troubleshooting; Data-driven decision making

What They're Looking For.

Must Have

10+ years in software, 5+ years in Technical Lead role, Python (FastAPI, Flask, or Django), React (TypeScript), Hands-on LLM integration, Prompt engineering, Orchestration frameworks, SQL/NoSQL skills, Vector Databases, Expert-level Azure or AWS experience, IaC (Terraform/icep), AI-ready CI/CD pipelines, REST expertise, Event-driven architectures expertise, MCP protocol expertise

Nice to Have

Experience integrating AI agents with Workday (HCM), Experience integrating AI agents with Power Platform, Familiarity with compliance-aware development, Mastery of Docker, Mastery of Kubernetes, Advanced understanding of secrets management, Advanced understanding of Security for AI

What You'll Do.

Architect AI-first systems

Guide technical evolution

Ensure engineering quality

Ensure solution scalability

Ensure delivery throughput

Provide hands-on leadership

Define engineering patterns

Uphold engineering patterns

Lead move to Agentic workflows

Ensure custom solutions are AI-first

Implement Model Context Protocol

Reinstate structured code reviews

Establish quality gates

Mentor junior engineers

Upskill junior engineers

Optimize cloud architectures

Balance model selection

Balance inference costs

Partner with Business partners

Scope work using semantic search

How You'll Work.

Team & Collaboration

Close partnership with product teams; Close partnership with delivery teams

Full Job Description

**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

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