Senior AI Engineer/AI Lead in India at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer/AI Lead based in India.
This role offers the opportunity to lead the development of advanced AI solutions that transform healthcare and clinical research operations.
You will design and implement intelligent multi-agent systems that improve the processing and management of safety data.
The position combines AI engineering, large language models, cloud technologies, and regulated industry expertise.
You will collaborate with technical teams, domain specialists, and quality stakeholders to build secure, scalable, and compliant AI platforms.
The role provides strong ownership over architecture decisions, AI governance, validation strategies, and innovation initiatives.
You will contribute to meaningful technology advancements while working in a fast-paced environment focused on improving patient safety.
The Senior AI Engineer/AI Lead will be responsible for designing, building, and scaling AI-driven platforms while ensuring technical excellence, regulatory alignment, and business impact. This role requires ownership of AI architecture, model implementation, evaluation frameworks, and collaboration across multidisciplinary teams.
- Design and implement multi-agent AI architectures using modern AI platforms, orchestration frameworks, and large language models.
- Define agent workflows, including orchestration strategies, communication patterns, state management, escalation handling, and audit trail capabilities.
- Develop and optimize prompt engineering strategies, including system prompts, examples, validation rules, and safety guardrails.
- Build Model Context Protocol (MCP) servers and secure integrations that enable AI agents to access enterprise applications, data sources, and services.
- Create evaluation pipelines by designing benchmarks, preparing validation datasets, and measuring model accuracy, reliability, and performance.
- Architect quality control mechanisms, including model verification, rule-based validation, and automated escalation processes.
- Support migration and improvement of existing AI solutions while enhancing prompts, workflows, and evaluation methodologies.
- Define CI/CD and MLOps strategies covering model lifecycle management, version control, monitoring, deployment pipelines, and cost optimization.
- Establish technical validation approaches aligned with regulated software standards and collaborate on qualification documentation.
- Produce and review technical documentation, including architecture decisions, AI specifications, and implementation guidelines.
- Collaborate with engineering, quality, regulatory, and business teams to ensure solutions meet compliance and operational requirements.
- Mentor junior engineers and contribute to technical strategy, innovation, and best practices across AI development initiatives.
The ideal candidate brings deep expertise in AI engineering, software development, and enterprise AI implementation, with the ability to deliver reliable solutions in complex and regulated environments.
- 7+ years of hands-on experience building production-grade AI or machine learning systems, including experience with large language model applications.
- Strong expertise in AI architecture, prompt engineering, LLM orchestration, and retrieval-augmented generation (RAG) approaches.
- Practical experience with large language model platforms, APIs, and frameworks for building AI-powered applications.
- Strong knowledge of AWS services, including Bedrock, Lambda, S3, IAM, CloudTrail, and cloud-based AI infrastructure.
- Experience developing multi-agent or multi-step AI workflows using frameworks such as LangGraph, LangChain, CrewAI, or similar technologies.
- Advanced Python programming skills with strong software engineering fundamentals, including API design, testing, containerization, infrastructure-as-code, and version control.
- Experience designing evaluation frameworks for AI outputs, including benchmarking, regression testing, accuracy measurement, and confidence evaluation.
- Ability to communicate complex technical concepts clearly to technical and non-technical stakeholders.
- Bachelor’s degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience.
- Experience with secure enterprise integrations and scalable AI system design.
Preferred qualifications:
- Experience building Model Context Protocol (MCP) servers or similar AI tool-serving architectures.
- Knowledge of regulated software environments, GxP requirements, GAMP5 validation, CSV/CSA methodologies, or FDA software guidance.
- Experience with healthcare, pharmaceutical, clinical research, or other regulated industries.
- Familiarity with document processing workflows, OCR, structured data extraction, or clinical text analysis.
- Knowledge of medical coding standards or healthcare data processing workflows.
- Proven experience delivering LLM-based solutions in production environments.
- Flexible work arrangements, including remote work opportunities.
- Opportunity to work on innovative AI solutions with meaningful healthcare impact.
- Exposure to advanced technologies including generative AI, cloud platforms, and AI agent frameworks.
- Continuous learning and professional development opportunities.
- Collaboration with diverse global teams across technology, healthcare, and research domains.
- Opportunity to influence AI strategy, architecture, and governance practices.
- Career growth opportunities within a technology-driven environment.