Sr Associate Software Engineer - Gen AI

Amgen; India; On-site; INR 3,500,000 - 5,200,000; Full time

Job summary

Amgen is seeking a Senior Associate Software Engineer to contribute hands-on software development for GenAI solutions, including LLM-powered assistants and RAG applications. You will design, implement, test, and deploy scalable AI capabilities on enterprise platforms, and collaborate across teams to ensure secure, reliable delivery.

Candidates should have 4+ years in software development and 2+ years building GenAI applications, with strong Python proficiency and experience in APIs, embeddings,

Qualifications

• 4+ years of professional experience in software development, application engineering, systems integration, or system design.
• 2+ years hands-on experience building, deploying, or supporting production GenAI applications, assistants, agents, or RAG solutions.
• Strong Python skills; experience with APIs, data services, or integration components.

Responsibilities

• Design, develop, test, and deploy LLM-powered assistants, agents, Custom GPTs, RAG solutions, APIs, and AI-enabled applications on approved platforms.
• Implement prompt and context strategies, embeddings, vector databases or search, and tool integration.
• Build scalable RAG pipelines that ground responses in trusted enterprise data.
• Contribute to GenAI capability roadmap with MCP-based Apps, ChatGPT Skills, plugins, and reusable integration patterns.
• Develop integration layers and event-driven workflows to connect systems and trigger agent workflows.

Skills

Python

GenAI apps

APIs

Agent orchestration

AWS

Embeddings

Retrieval pipelines

Education

Any degree

Tools

GitHub Copilot

OpenAI Codex

CI/CD

Job description

About Amgen

Amgen harnesses the best of biology and technology to fight the world's toughest diseases, and make people's lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what's known today.

About the Role

The Senior Associate Software Engineer is a hands‑on software engineering contributor within the Applied AI - AI Productivity and Custom GPT Solutions Practice. The role designs, develops, tests, deploys, and supports secure, scalable, intuitive, and reusable GenAI solutions, including LLM‑powered assistants, agents, Custom GPTs, retrieval‑augmented generation (RAG) applications, and associated AI capabilities on approved enterprise platforms.

Responsibilities

GenAI Solution Delivery

• Design, develop, test, and deploy LLM‑powered assistants, agents, Custom GPTs, RAG solutions, APIs, and AI‑enabled applications on ChatGPT Enterprise and other approved platforms.
• Implement prompt and context strategies, structured outputs, embeddings, vector or hybrid retrieval, tool calling, workflow orchestration, and human‑in‑the‑loop controls.
• Build scalable RAG pipelines that ground responses in trusted enterprise data.
• Contribute to the GenAI capability roadmap through implementation of MCP‑based Apps, ChatGPT Skills, plugins, Workspace Agents, and reusable integration patterns.
• Develop integration layers and event‑driven workflows using APIs, RPA, n8n, and approved orchestration tools to connect systems and trigger agent workflows.
• Develop reusable Python services, libraries, templates, and evaluation utilities, and contribute TypeScript, React, or Next.js components when required by the solution.

Quality, Security, and Operations

• Implement automated unit, integration evaluation, and end‑to‑end tests, along with tracing and monitoring for retrieval quality, response consistency and reliability.
• Implement safeguards for prompt injection, data leakage, unauthorized retrieval, insecure tool execution, secrets exposure, excessive agency, and inappropriate model outputs.
• Apply secure integration and identity patterns using API gateways, OAuth, service identities, delegated authorization, role‑based access control, secrets management, least privilege, and user‑level auditability.
• Build and maintain CI/CD pipelines and approved cloud deployment configurations using AWS services, containers, serverless compute, or managed platform capabilities.
• Troubleshoot defects across application, model, retrieval, data, integration, and infrastructure layers; support incident investigation, remediation, rollback, patching, and performance tuning.
• Create and maintain technical designs, test evidence, runbooks, deployment instructions, and handover materials that support sustainable operations.

Collaboration and Enablement

• Partner with functional teams, product owners, architects, business SMEs, data engineers, platform teams, DevOps, cybersecurity, privacy, and responsible AI stakeholders to translate requirements into reliable solutions.
• Participate in agile planning, backlog refinement, estimation, demonstrations, retrospectives, release activities, and technical design reviews.
• Review code and technical designs, apply software engineering standards, and use AI‑assisted development tools such as OpenAI Codex or GitHub Copilot with appropriate review, security, and quality controls.
• Support office hours, technical enablement sessions, junior engineers, and knowledge‑sharing through reusable examples, engineering patterns, and lessons learned.
• Communicate delivery status, technical risks, dependencies, defects, and recommendations clearly to technical and non‑technical stakeholders.

Required Skills and Qualifications

Basic Qualifications

• Any degree and 5 to 9 years of relevant experience in Computer Science, Information Technology, Engineering, Data Science, or a related field

Must‑Have Skills

• 4 or more years of professional experience in software development, application engineering, systems integration, or system design.
• 2 or more years of hands‑on experience building, deploying, or supporting production GenAI applications, assistants, agents, Custom GPTs, RAG solutions, or comparable AI‑enabled software.
• Strong hands‑on proficiency in Python and experience developing, testing, debugging, and maintaining production applications, APIs, data services, or integration components.
• Hands‑on experience with prompt and context design, embeddings, vector databases or search, retrieval pipelines, structured outputs, tool integration, agent orchestration, evaluation, guardrails, and observability.
• Experience designing and building cloud‑native solutions, preferably on AWS, using services such as Amazon B