Forward Deployment Engineer (AI)

Location: Gurgaon, Noida, Pune, Hyderabad, or Bangalore, India

Company

hirify.global delivers technology and consulting solutions for pharmaceutical and life sciences organizations.

What you will do

• Embed directly in pharma client organizations and own the end-to-end design, build, and deployment of production AI systems on client infrastructure.
• Lead technical workstreams and direct Agent Pipeline Engineers and AI-Augmented Engineers.
• Design multi-agent AI systems using orchestration, tool integration, RAG, memory, human-in-the-loop workflows, evaluation pipelines, and production MLOps.
• Build with Databricks, Snowflake, AWS, Bedrock Agents, SageMaker, and the Claude and Anthropic API stack with Model Context Protocol.
• Translate commercial and clinical pharma problems into explainable AI architectures and validate outputs against domain requirements.
• Contribute reusable deployment patterns, reference architectures, accelerators, technical standards, and delivery methodology.

Requirements

• 8+ years of experience in engineering, data engineering, analytics engineering, or AI/ML roles, including substantial direct pharma or life sciences client exposure.
• Pharma domain experience is mandatory, with commercial expertise in areas such as SFE, incentive compensation design, market access, omnichannel, KAM, or patient services, or clinical expertise in trial operations, CDASH/SDTM, site analytics, RWE, HEOR, or regulatory data.
• Production AI engineering experience is required, including shipped LLM agents, RAG pipelines, multi-agent workflows, or clinical AI systems used by real users in regulated environments.
• Strong foundations in Python, SQL, cloud infrastructure on AWS, Azure, or GCP, data pipeline architecture, and API design.
• Depth in at least one of Databricks, Snowflake, AWS Bedrock, or the Claude and Anthropic API stack, with working fluency across the others.
• Ability to scope ambiguous problems, present architecture decisions to senior stakeholders, work independently, and deliver in sprint-based cycles.

Nice to have

• Experience in technology consulting, systems integration, or AI services delivery for pharma or life sciences clients.
• Experience leading engineering teams of three or more people across concurrent AI workstreams.
• Familiarity with AI governance, responsible AI, FDA AI/ML guidance, ICH guidelines, and GxP data integrity requirements.
• AWS Certified AI Practitioner, Databricks Certified Generative AI Engineer Associate, SnowPro Advanced Data Engineer, or Claude Certified Architect Foundations certification.

Culture & Benefits

• Forward deployment directly within client environments rather than external advisory work.
• High-velocity delivery cycles focused on defining, engineering, and shipping scope within weeks.
• Opportunities to mentor junior FDEs and AI-Augmented Engineers.
• Contributions to a growing institutional library of pharma AI deployment patterns and reusable accelerators.