{"id":186404,"url":"https://alion.io/job/ge-vernova-lead-engineer-ai-engineering-2","title":"Lead Engineer - AI Engineering","company":{"id":6165,"name":"GE Vernova","domain":"gevernova.com","url":"https://alion.io/company/ge-vernova","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":368,"ghost_share":0.003,"stale_share":0.685,"repost_share":0.033,"time_to_fill_p50_days":27,"computed_at":"2026-10-25T05:49:26Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":25000,"max_usd":67000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":44},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Go","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NLP","optional":false},{"name":"Node JS","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"TensorFlow","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-09-01T17:54:06Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-10-23T03:15:43Z","board_verified":false,"closed_at":null,"days_open":54,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":54},"description":"Job Description Summary\nGE Vernova is embracing cutting-edge technologies to streamline operations, improve customer experiences, and drive growth. As part of this vision, we are building a dedicated team to leverage Generative AI and redefine how we engage with our industry. The ultimate goal of the team is to automate prompting, develop a framework for prompting across use cases to maximize reuse as well as sharing across businesses.We are seeking a highly motivated and talented AI Engineer to join our dynamic team. The successful candidate will be responsible for creating and optimizing prompts for LLMs, collaborating with domain experts and end users to develop software solutions that address both internal and external needs. This position offers a great opportunity to work at the intersection of advanced technology and traditional industry, making a tangible impact on our business processes.\nAs a GE Vernova accelerator, AI Foundry is driving strategy and leading research & development efforts to execute on the business’s mission to help power the energy transition. We forge the collaborations and help invent the technologies required to electrify and decarbonize for a zero-carbon future.\nRepresenting virtually every major scientific and engineering discipline, our researchers are collaborating with GE Vernova’s businesses, the U.S. government, and more than 420 entities at the forefront of technology to execute on 150+ energy-focused projects. Collectively, these research programs and initiatives aim to solve near term technical challenges, deliver next generation product advances, and drive long term breakthrough innovation to enable more affordable, reliable, sustainable, and secure energy.\nJob Description\nKey Responsibilities:\nDesign, implement, and optimize AI Agents using LLMs, reinforcement learning, planning algorithms, and decision-making frameworks.\n\nDevelop scalable multi AI Agent architectures supporting long horizon reasoning, autonomy, planning, interaction, and complex task completion.\n\nIntegrate AI Agents with APIs, backend services, databases, and enterprise applications.\n\nPrototype, deploy, and maintain AI-driven systems ensuring reliability and performance in production environments.\n\nOptimize agent behavior through continuous feedback, reinforcement learning, and user interaction.\n\nCollaborate closely with research, engineering, product, and deployment teams to iterate on agent capabilities and innovate continuously.\n\nMonitor AI Agent performance, conduct rigorous evaluations, implement safety guardrails, and ensure ethical AI practices.\n\nDocument AI Agent architectures, design decisions, workflows, and maintain comprehensive technical documentation.\n\nStay current with emerging AI technologies, contribute to platform and tooling improvements, and share knowledge within the team.\n\nYour mission is to push the boundaries of planning, reasoning, and agentic intelligence. You will design and implement large-scale AI/ML solutions integrating the latest state of the art research in our global products\n\nCore Technical Skills:\nProficiency in Python and/or languages like JavaScript, TypeScript, Node.js, or Java, Go, with strong coding and software engineering practices.\n\nExpertise with AI/ML libraries and frameworks such as LangChain, OpenAI APIs, PyTorch, TensorFlow, commercial or open source LLMs.\n\nHands-on experience with LLMs, prompt engineering, and natural language processing (NLP).\n\nKnowledge of agent orchestration platforms and multi-agent systems (e.g., AutogenAI, LangGraph, MCP protocol).\n\nFamiliarity with data management, vector databases, semantic retrieval, and real-time data pipelines.\n\nExperience deploying AI systems on cloud platforms (AWS, Google Cloud) with container orchestration (Docker, Kubernetes).\n\nStrong understanding of machine learning model training, fine-tuning, and evaluation techniques.\n\nAwareness of AI ethics, data privacy, and secure handling of sensitive information.\n\nQualifications:\nMasters' degree in Computer Science, AI/ML, Engineering, Mathematics, or related field with 3+ years of relevant experience.\n\nThorough experience in AI, GenAI application development & deployment particularly with autonomous agent systems or related AI software engineering roles.\n\nDemonstrated ability to work independently in fast-paced, experimental environments.\n\nHands-on experience designing and building GenAI apps that allow users to experience AI use cases supporting features like agent orchestration, multi-step reasoning, prompt engineering, RAG integration, and model selection\n\nExpertise with LLMs and deep learning models, machine learning lifecycle management, data generation methods, model training & validation coupled with strong fundamentals and passion in software engineering and system architecture\n\nMust be willing to work out of an office located in Bangalore\n\nMust be 18 years or older.\n\nYou must submit your application for employment on the careers page at www.careers.gevernova.com to be considered.\n\nAdditional Information\nRelocation Assistance Provided: Yes","description_format":"text","description_chars":5093,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Relocation assistance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Industrial Machinery","Wind Energy","Smart Grid","Nuclear Engineering"],"lifecycle":[{"event":"open","at":"2026-09-01T17:54:06Z"}],"visa":[],"liveness":{"score":15,"band":"cold","label":"Long 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