Role Overview :

We are looking for an experienced Senior AI/ML Engineer with strong hands-on expertise in Generative AI, Agentic AI, LLMs, RAG, AI evaluation, cloud-native engineering, and solution architecture. The role will involve designing, developing, evaluating, and deploying production-grade AI solutions while working closely with business and technical stakeholders to translate complex and ambiguous requirements into scalable, secure, and reliable solutions.

Key Responsibilities :

- Design, develop, and deploy production-grade AI/ML and Generative AI solutions for complex business use cases.

- Build and integrate LLM-powered applications, AI agents, copilots, intelligent automation, and agentic workflows.

- Design and implement scalable RAG pipelines, including data ingestion, chunking, embeddings, retrieval, context management, and response generation.

- Develop and optimize prompt engineering, orchestration, tool/function calling, and agent workflows.

- Design and implement AI evaluation frameworks, including evaluation datasets, scoring methodologies, rubrics, agent-performance testing, and failure-mode analysis.

- Establish mechanisms to measure and improve accuracy, relevance, reliability, safety, latency, and overall AI solution performance.

- Design scalable, resilient, and secure cloud-native AI architectures using modern distributed systems and microservices principles.

- Develop and manage Infrastructure as Code (IaC) for AI solutions and cloud environments, particularly on Microsoft Azure.

- Build and maintain APIs, services, data integrations, and supporting components required for enterprise AI applications.

- Translate business and technical requirements into solution architectures, system designs, technical specifications, and implementation plans.

- Lead technical discovery sessions with clients and stakeholders to understand business problems, identify AI opportunities, and define practical solution approaches.

- Take AI solutions from prototype/PoC through production deployment, monitoring, optimization, and support.

- Collaborate with Data Engineering, Product, Architecture, Cloud, Security, and business teams to deliver end-to-end solutions.

- Conduct technical design reviews and code reviews and promote reusable engineering patterns and best practices.

- Troubleshoot complex issues across AI applications, APIs, data pipelines, cloud infrastructure, and distributed systems.

- Optimize AI workloads for scalability, performance, reliability, latency, and cost.

- Mentor engineers and contribute to team capability development in modern AI/ML and cloud technologies.

- Stay current with advancements in LLMs, Agentic AI, AI evaluation, AI engineering practices, and Azure AI services.

Required Skills & Experience :

- 5 - 10 years of experience in software engineering, AI/ML engineering, or related technology roles.

- Strong hands-on experience with Python or an equivalent programming language.

- Proven experience building and deploying AI/ML solutions in production environments.

- Strong understanding of LLMs, Generative AI, prompt engineering, and model deployment.

- Hands-on experience with Agentic AI, AI agents, LLM workflows, copilots, or intelligent automation.

- Strong experience designing and implementing RAG-based solutions.

- Hands-on experience with AI/LLM evaluation, including evaluation datasets, scoring/rubrics, model or agent testing, and failure analysis.

- Strong understanding of distributed systems, microservices, APIs, and cloud-native architecture.

- Hands-on experience with Infrastructure as Code (IaC) in cloud environments, particularly Azure.

- Experience with modern AI/ML frameworks, APIs, and enterprise data-integration patterns.

- Strong solution architecture and system design capabilities.

- Advanced understanding of the AI Development Lifecycle (AI-DLC) and production AI engineering practices.

- Experience designing secure, scalable, and maintainable AI solutions.

- Proven experience participating in or leading client discovery, solution design, and technical delivery.

- Strong stakeholder-management skills across technical, business, and executive audiences.

- Excellent communication, presentation, problem-solving, and storytelling skills.

- Ability to structure ambiguous business and technical problems into actionable solution approaches.

- Strong ownership mindset with the ability to independently drive AI initiatives from concept to production.

Preferred / Good to Have :

- Master's degree in AI/ML, Data Science, Computer Science, Software Engineering, or a related discipline.

- Experience with React / Next.js for AI-enabled user interfaces.

- Knowledge of healthcare data, regulatory requirements, interoperability, or healthcare technology.

- Experience with Adobe Experience Platform (AEP) or enterprise Marketing Technology platforms.

- Exposure to LLM observability, AI governance, responsible AI, and model monitoring.

- Experience with major AI/cloud platforms such as Azure OpenAI, AWS, or GCP.