Forward Deployed Engineer/ Agentic AI Solutions engineer

Job Description: AI Solutions Engineer Bloom Energy faces an unprecedented opportunity to change the world and the way energy is generated and delivered.  Our mission is to make clean, reliable energy affordable globally.  Bloom’s Energy Server delivers highly reliable and resilient, always-on electric power that is clean, cost-effective, and ideal for micro grid applications.  We are helping our customers power their operations without disruption and combustion. We are looking for AI Solutions Engineer to join our team in one of today’s most exciting technologies.  This role would report to the Business Intelligence Manager and based in Bengaluru / Mumbai, India. The AI Solutions Engineer will support the Services Business Intelligence team to develop AI/ML solutions and automation into our service strategy. This will include building and deploying machine learning algorithms (for applications to support predictive maintenance and process optimization) and developing AI solutions (agents), process automations and enhanced analytics.  Requirements: ·       2-4 years of hands-on experience building AI/ML solutions in a production or near-production environment ·       Strong proficiency in Python – you write clean, production-grade code, not just notebooks ·       Working experience with LLMs and generative AI: prompt engineering, RAG architecture, agentic workflows, or conversational AI systems ·       Strong SQL skills and experience working with relational databases and data warehouses ·       Experience with cloud platforms (AWS strongly preferred – Bedrock, Lambda, S3, Redshift, ECS/EKS) ·       Familiarity with at least one orchestration/agentic framework: LangChain, LanGraph, CrewAI, AuguGen, or similar ·       Understanding of data modeling, ETL/ELT pipelines, and working with messy, imperfect enterprise data ·       Strong communication skills – ability to explain technical concepts to non-technical stakeholders Strong Plus: ·       Experience with vector databases and knowledge graphs ·       Hands-on experience with AWS Bedrock ·       Experience building multi-system integrations across enterprise platforms ·       Exposure to AI governance: audit logging, RBAC, confidence scoring, human-in-the-loop workflows, hallucination prevention ·       Experience with MCP or similar tool-use protocols Responsibilities: Agentic AI Development ·       Design, build, and iterate on agentic AI workflows using frameworks such as LanGraph, CrewAI, or equivalent orchestration tools ·       Develop retrieval-augmented generation (RAG) pipelines that ground LLM responses in approved enterprise data sources with source citation, confidence scoring, and traceability ·       Build and maintain multi-agent systems that decomposes complex operational questions into sub-tasks, query structured/unstructured data, and synthesize actionable outputs