Senior Forward Deployed Engineer (AI / ML), AI Studio

India - Hyderabad

JOB ID: R-251200 LOCATION: India - Hyderabad WORK LOCATION TYPE: On Site DATE POSTED: Aug. 05, 2026 CATEGORY: Information Systems

CAREER LEVEL:GCF 5 – Specialist

CAREER TRACK:Individual Contributor

PRIMARY SCOPE:End-to-end technical delivery ownership of a small AI or automation solution or substantial deployment workstream

ORGANIZATION:Applied AI AI Studio

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases and make people’s lives easier,fullerand longer. We discover, develop,manufactureand deliver innovative medicines to help millions of patients. Amgen helpedestablishthe biotechnology industry more than 40 years ago andremainsat thecutting edgeof innovation, using technology and human genetic data to push beyond what is known today.

ABOUT THE ROLE

Role Description:

The Senior Forward Deployed Engineeroffers a unique opportunity to join a fun, innovative engineering team within the AI & Data Science (AI&D) - organization. We are the Applied AI team (AI Studio). AI Studio is Amgen’s enterprise engine for turning high-value business challenges into scalable AI products. We partner with key business partners across the company toidentifythe right opportunities, shape them into actionable use cases, and design, build, and launch AI products responsibly. Our work spans the full lifecycle from early discovery and rapid prototyping to production deployment, reuse across the enterprise, and measurable business impact.You willbe part of AI Studioleadingthe technical delivery of complex AI and automation solutions throughdiscovery, solution design, build, evaluation, production deployment, early stabilization and measurable value,production deployment, earlystabilizationand measurable value.

You willmaintaintechnical continuity across the lifecycle, working with business stakeholders and multidisciplinary teams to shape the simplestviablesolution, coordinate execution, make delivery trade-offs, removeblockersand contribute hands-on to critical components. The role combines enterprise solution engineering, applied AI/ML, GenAI, RAG and agents, integration, evaluation,MLOps/LLMOps, security,governanceand production operations. Technical accountability complements, but does not replace, explicit product, business,complianceand long-term support ownership.

Roles & Responsibilities:

• Lead discovery by clarifying the business workflow, users, intended outcome, value hypothesis, acceptance criteria, operational constraints, data readiness, integrationdependenciesand production implications;

• Translatecomplexproblems into an executable solution design, delivery plan, technical workstreams, estimates, milestones, dependencies, risks, acceptance criteria, releaseapproachand support transition.

• Build, prototype, review or contribute to critical production components to prove feasibility or unblock delivery, including AI-enabled applications, RAG, bounded agents, intelligent automation,APIsand integrations.

• Define andmaintainthe integrated architecture across applications, workflows, data and knowledge pipelines, models, retrieval, agents, APIs, enterprise integrations, identity, access controls,observabilityand human review.

• Orchestrate delivery across full-stack engineering, data science, ML and context engineering, testing, platform, security,complianceand business roles;

• Establish integrated testing, AI evaluation and governance covering functional, performance, security, data, model, retrieval, generation, tool-use, human-oversightand operational behaviour with explicit release thresholds.

• Coordinate production readiness through CI/CD, staged release, monitoring, logging, SLOs, rollback, recovery,runbooksand controlled deployment; support early issue triage,stabilizationand transition to the operating owner.

• Communicate evidence, risks,trade-offsand status clearly; measure adoption and value and convert delivery lessons into reusable components, accelerators, standards,documentationand playbooks.

Basic Qualifications and Experience:

• Bachelor’s/Master’sdegree with 8 - 13years of experience in Computer Science,ITor related field.

Functional Skills:

• Technical discovery, and value framing: Workflow analysis, intended-use definition, feasibility assessment, data and integration readiness, success measures, estimates, dependencymappingand technical go/no-go recommendations.

• Enterprise solution architecture…