Sr Associate Software Engineer - Gen AI

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Sr Associate Software Engineer - Gen AI

Amgen

Hyderabad / Atlanta

5-9 years

Today

$42.2K–63.9K/yr

Full-time

Onsite

Skills Required

LLM

RAG

Gen AI

OpenAI

ChatGPT Enterprise

Custom GPTs

Embeddings

Vector Database

Retrieval Pipelines

LangChain

Python

APIs

Tool Calling

Agent Orchestration

MCP

Description

Amgen is hiring a Senior Associate Software Engineer for its Applied AI - AI Productivity and Custom GPT Solutions Practice. The role focuses on building secure, scalable GenAI solutions and supporting their delivery, operations, and enablement.

Company: Amgen

Role: Sr Associate Software Engineer - Gen AI

Location: India - Hyderabad | On Site

Experience

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

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

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

Experience designing secure RESTful or GraphQL integrations using API gateways, OAuth, service identities, enterprise authentication, role-based access, secrets management, and least-privilege principles

Experience with automated testing, source control, code review, Git-based workflows, CI/CD, and responsible use of AI-assisted software development tools

Experience building modern web applications using TypeScript, React, Next.js, component-driven architecture, state management, design systems, and API integration

Working knowledge of SQL, files, databases, and governed data-access patterns

Strong troubleshooting and analytical skills across application, model, data, integration, and infrastructure layers

Strong verbal and written communication skills

Ability to collaborate effectively with global, distributed, cross-functional teams using agile or scaled agile ways of working

High degree of initiative, adaptability, ownership, and self-motivation

Ability to manage multiple priorities, assess gaps and fit, communicate technical risks and tradeoffs, and support shared team outcomes

Qualification

Any degree

Responsibilities

Design, develop, test, deploy, and support secure, scalable, intuitive, and reusable GenAI solutions

Build LLM-powered assistants, agents, Custom GPTs, retrieval-augmented generation applications, and associated AI capabilities on approved enterprise 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 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

Contribute TypeScript, React, or Next.js components when required by the solution

Implement automated unit, integration, evaluation, and end-to-end tests with tracing and monitoring

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

Create and maintain technical designs, test evidence, runbooks, deployment instructions, and handover materials

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 with appropriate review, security, and quality controls

Support office hours, technical enablement sessions, junior engineers, and knowledge-sharing

Communicate delivery status, technical risks, dependencies, defects, and recommendations clearly to technical and non-technical stakeholders

Additional Responsibilities

Support incident investigation, remediation, rollback, patching, and performance tuning

Nice To Have

Experience with OpenAI APIs and SDKs

MCP servers and Apps

LangChain

LangGraph

comparable agent technologies

Amazon Bedrock and related agent capabilities

AWS EC2

VPC networking

Databricks

Unity Catalog

Vector Search

SQL Warehouses

semantic layers

governed natural-language-to-SQL solutions

Power Automate

UiPath

Tableau

Jira

Smartsheet

model and application evaluation

red teaming

responsible AI

AI security

GxP

computer-system validation

regulated technology environments

relevant technical certifications

More Skills

LLM-powered assistants, agents, retrieval-augmented generation (RAG), AI-enabled applications, prompt design, context design, structured outputs, search, workflow orchestration, human-in-the-loop controls, MCP-based Apps, ChatGPT Skills, plugins, Workspace Agents, RPA, n8n, TypeScript, React, Next.js, unit testing, integration testing, end-to-end testing, tracing, monitoring, prompt injection safeguards, data leakage safeguards, unauthorized retrieval safeguards, insecure tool execution safeguards, secrets management, least privilege, CI/CD, AWS, Amazon Bedrock, AWS Lambda, Amazon EKS, ECS, API Gateway, IAM, networking, event-driven integration, RESTful integrations, GraphQL integrations, OAuth, service identities, role-based access control, Git, code review, AI-assisted development tools, OpenAI Codex, GitHub Copilot, SQL, databases, cloud deployment, containers, serverless compute, managed platform capabilities, runbooks, deployment instructions, technical designs, agile, scaled agile

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