Develop scalable multi AI Agent architectures supporting long horizon reasoning, autonomy, planning, interaction, and complex task completion.
Integrate AI Agents with APIs, backend services, databases, and enterprise applications.
Your 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
Monitor AI Agent performance, conduct rigorous evaluations, implement safety guardrails, and ensure ethical AI practices.
Stay current with emerging AI technologies, contribute to platform and tooling improvements, and share knowledge within the team.
Prototype, deploy, and maintain AI-driven systems ensuring reliability and performance in production environments.
Document AI Agent architectures, design decisions, workflows, and maintain comprehensive technical documentation.
Collaborate closely with research, engineering, product, and deployment teams to iterate on agent capabilities and innovate continuously.
Design, implement, and optimize AI Agents using LLMs, reinforcement learning, planning algorithms, and decision-making frameworks.
Optimize agent behavior through continuous feedback, reinforcement learning, and user interaction.
Requirements
aws
docker
llms
langchain
python
master’s
Experience deploying AI systems on cloud platforms (AWS, Google Cloud) with container orchestration (Docker, Kubernetes).
Hands-on experience with LLMs, prompt engineering, and natural language processing (NLP).
Hands-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
Must be willing to work out of an office located in Niskayuna, NY.
Expertise with AI/ML libraries and frameworks such as LangChain, OpenAI APIs, PyTorch, TensorFlow, commercial or open source LLMs.
Strong understanding of machine learning model training, fine-tuning, and evaluation techniques.
Demonstrated ability to work independently in fast-paced, experimental environments.
Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, AI Engineering, or related fields.
Minimum 2-3 years of experience in AI, GenAI application development & deployment particularly with autonomous agent systems or related AI software engineering roles.
Expertise 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
Legal authorization to work in the U.S. is required. We will not sponsor individuals at the Bachelor’s level for employment visas, now or in the future, for this job opening.
Awareness of AI ethics, data privacy, and secure handling of sensitive information.
Proficiency in Python and/or languages like JavaScript, TypeScript, Node.js, or Java, Go, with strong coding and software engineering practices.
Knowledge of agent orchestration platforms and multi-agent systems (e.g., AutogenAI, LangGraph, MCP protocol).
Must be 18 years or older.
Familiarity with data management, vector databases, semantic retrieval, and real-time data pipelines.
Benefits
Information not given or found
Training + Development
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Interview process
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Visa Sponsorship
no visa sponsorship will be provided; candidates must already have u.s. work authorization.
Security clearance
employment offer contingent on successful drug screening.
Company
Overview
April 2024
Founded
The company emerged from the spin-off of GE's energy units in April 2024.
>$10B Quarterly Revenue
Revenue Growth
Achieves over $10 billion in quarterly revenue, driven by demand for power infrastructure and digital solutions.
$3B
Wind Turbine Backlog
Maintains a significant backlog in wind turbine orders, reflecting strong market demand.
25%
Global Electricity Supply
Contributes to generating 25% of the world’s electricity through its installed turbines and grids.
Traces roots back to Edison and Alstom, merging power, renewable, digital & financial wings.
Headquartered in Cambridge, MA, crafts large-scale gas turbines, SMRs, wind turbines, hydro and grid tech to fuel economies.
On the nuclear front, advancing small modular reactors (like BWRX‑300) in partnership with utilities and supporting semiconductor projects.
Wind prowess spans onshore, offshore and blade making—with key sites like Dogger Bank offshore and blade plants in Spain.
Electrification arm tackles grid stability: HVDC, transformers, storage, conversion, plus GridOS software powering smarter infrastructure.
Weaves finance and consulting through energy-infrastructure investments, funding solar farms to pipelines via GE Energy Financial Services.
Culture + Values
Relentlessly focused on advancing the world’s transition to cleaner, more sustainable energy.
Believes in working with customers, partners, and communities to create innovative energy solutions that make a meaningful difference.
Prioritizes excellence, integrity, and accountability in everything they do.
Committed to driving real change through technology and partnerships that will transform the global energy landscape.
Environment + Sustainability
2050 target
Net zero commitment
Committed to achieving net zero carbon emissions by 2050.
Focused on reducing emissions through advanced energy technologies.
Maximizing use of renewable energy sources and leveraging digital solutions for energy efficiency.
Solutions aim to decarbonize industries and help customers meet their sustainability goals.