Forward Deployed Engineer/ Agentic AI Solutions engineer

Overview

Join Bloom Energy's Services Business Intelligence team to develop AI/ML solutions, agentic AI workflows and process automation that support predictive maintenance and process optimization for clean, reliable energy systems.

What you'll do

• Design, build, and iterate on agentic AI workflows using frameworks such as LangGraph, 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 decompose complex operational questions into sub-tasks, query structured and unstructured data, and synthesize actionable outputs.
• Implement prompt engineering, prompt libraries, and evaluation harnesses to ensure response quality, accuracy, and governance compliance.
• Integrate with enterprise LLMs (e.g. AWS Bedrock / Anthropic Claude, OpenAI) and manage model abstraction layers for flexibility.
• Build connectors and data pipelines to ingest and query data across different operational systems.
• Develop and maintain semantic layers, knowledge graphs, and vector databases for contextual retrieval.
• Implement data quality checks, trusted-source hierarchies, and conflict resolution logic when multiple systems provide contradictory data.
• Support MCP or equivalent server integrations for live system connectivity.
• Build and deploy ML models for predictive maintenance, performance optimization, anomaly detection, and operational forecasting.
• Develop automated reporting, dashboards, and self-service analytics tools.
• Apply statistical methods to identify patterns, root causes, and actionable insights from fleet and service data.
• Partner with cross-functional teams to translate operational pain points into AI-enabled solutions.
• Contribute to the Agent Factory by building reusable connectors, templates, governance patterns, and deployment blueprints that scale across future service AI agents.
• Document architecture, data flows, and solution designs for knowledge transfer and production handoff.
• Support vendor collaboration and POC evaluation for enterprise AI partnerships.

What you'll need

• 2-4 years of hands-on experience building AI/ML solutions in a production or near-production environment.
• Strong proficiency in Python, writing 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, LangGraph, CrewAI, AuguGen, or similar.
• Understanding of data modeling, ETL/ELT pipelines, and working with messy, imperfect enterprise data.
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Graduate education in BA/BS/MA in Computer Engineering, Computer Science, Data Science or equivalent.

Nice to have

• 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.

Details

• Location: Bengaluru / Mumbai, India.
• Reports to the Business Intelligence Manager.