LikeRemoteSenior Agentic AI Engineer
from
$120,800.00 - $170,800.00
We are seeking an experienced Senior Generative AI Developer to help drive the design, development, and integration of state-of-the-art Generative AI andagentic AI solutions across our enterprise Controls Technology platform. You will collaborate with cross-functional teams, contribute deep technical expertise in context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration, and play a key role in delivering scalable, grounded AI solutions to enhance automation and operational efficiency. This role centers on architecting robust applications and agent systems on top of pre-trained and hosted foundation models — not on training or fine-tuning models.
Key Responsibilities
Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges.
Architect advancedcontext engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production.
Design and implement advanced generative AI methods, including sophisticatedprompt engineering andRetrieval-Augmented Generation (RAG).
Build and optimizeRAG systems, including hybrid search, multi-vector retrieval, and re-ranking pipelines.
Design and implementknowledge graphs andGraph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains.
Architectagentic workflows and multi-agent systems usingGoogle Agent Development Kit (ADK) and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer.
Design robustagent harnesses — governance, constraints, feedback loops, state/session management, and execution controls that make long-running agent systems reliable and safe.
Integrate agents with tools and data via theModel Context Protocol (MCP) and orchestrate inter-agent collaboration and task delegation via theAgent2Agent (A2A) protocol.
Support the integration of GenAI and agentic applications into production environments, ensuring robust deployment, scalability, observability, and maintainability.
Contribute to the development and optimization of real-time and streaming AI solutions.
Stay current with the latest advances in generative and agentic AI and actively share knowledge with the team.
Ensure adherence to ethical AI guidelines, guardrails, agent isolation/sandboxing, data privacy, and compliance standards.
Mentor junior team members, provide code reviews, and foster a culture of technical excellence.
Required Technical Skills
6+ years of experience in AI/software development, including significant experience in Generative AI and agentic AI.
Strong skills inPython and experience with data preprocessing, document ingestion, and API development.
Deep, hands-on expertise incore generative AI concepts — foundation models, LLMs, embeddings, tokenization, and context-window management.
Proficiency withmajor GenAI APIs (OpenAI, Gemini, Claude, etc.) and orchestration frameworks such asLangChain and LlamaIndex.
Advanced skills inprompt engineering andcontext engineering, including familiarity with prompt design tools/frameworks and dynamic context orchestration.
Proficiency withvector databases and embedding models for large-scale retrieval.
Strong experience buildingRAG systems, including chunking strategies, hybrid search, and multi-vector retrieval.
Practical experience designingknowledge graphs andGraph RAG pipelines (e.g., using graph databases such as Neo4j or ArangoDB) for relationship-aware, multi-hop retrieval.
Proven experience buildingagentic AI systems withGoogle ADK and/or comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI, OpenAI Agents SDK), including tool/function calling, planning, and memory.
Strong grasp ofmulti-agent orchestration patterns (supervisor/worker, hierarchical, peer-to-peer) andharness engineering (governance, feedback loops, execution controls, agent isolation/sandboxing).
Hands-on experience withagent interoperability protocols — theModel Context Protocol (MCP) for tool/data access and theAgent2Agent (A2A) protocol for inter-agent collaboration.
Experience withagent observability and evaluation (e.g., tracing, OpenTelemetry-based tooling) for production agent systems.
Experience working with AWS (or equivalent) cloud infrastructure for AI/GenAI.
Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for AI/agentic applications.
Strong skills inNLP (NER, dependency parsing, text classification, topic modeling).
Solid understanding of AI compliance, guardrails, and responsible AI practices.
Demonstrated portfolio of successful AI-driven projects in a business environment.
Required Soft Skills
Strong collaboration skills to work effectively in cross-functional teams.
Analytical and proactive approach to problem-solving.
Clear communication skills for both technical and non-technical audiences.
Eagerness to learn, innovate, and mentor less experienced developers.
Education:
Bachelor’s degree/University degree or equivalent experience
Master’s degree preferred
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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Job Family Group:
Technology------------------------------------------------------
Job Family:
Applications Development------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Primary Location Full Time Salary Range:
$120,800.00 - $170,800.00------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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This job opening is for an existing job vacancy.
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