AI/ML Solutions Architect (Agentic Systems)
Job Family:
IT Architecture/Cloud Travel Required:
None Clearance Required:
Ability to Obtain Public Trust
We are seeking an AI/ML Solutions Architect (Agentic Systems) to design and deliver secure, scalable, and cost-effective cloud-native AI solutions for federal clients. You will bridge complex mission needs and modern technology by owning end-to-end architectures and leading hands-on implementation—especially for agentic AI systems, RAG-based applications, and production-grade ML pipelines .
This role blends technical vision + practical delivery leadership : selecting tools, defining architectures, establishing engineering standards, and guiding implementation through prototypes, code reviews, and reference solutions.
What You Will Do:
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Design and implement agentic AI systems that enable autonomous decision-making, workflow orchestration, and mission process optimization—with appropriate guardrails and human oversight.
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Develop Generative AI applications for summarization, extraction, predictive insights, and conversational interfaces.
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Build and maintain scalable data pipelines integrating structured + unstructured data to support analytics and AI workloads.
- Apply advanced statistical and machine learning techniques to decision support and policy/program evaluation.
- Lead AI initiatives spanning:
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Retrieval-Augmented Generation (RAG) and evaluation
- Re-ranking strategies and retrieval quality optimization
- Prompt engineering, safety patterns, and defensive design
- Knowledge graph integration and graph-enhanced retrieval
- AI chatbots and conversational agents
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Fine-tune embeddings and LLMs (when appropriate) to improve domain performance, accuracy, robustness, and retrieval quality.
- Build entity graphs using entity resolution (matching, deduplication, linking, relationship discovery) to enable graph analytics and enhanced retrieval.
- Collaborate across engineering, security, and stakeholders to prototype rapidly , iterate responsibly, and deliver mission-ready outcomes.
- Lead deployment in AWS-first cloud environments , leveraging Infrastructure-as-Code, DevOps/DevSecOps, and operational excellence patterns.
- You will own and drive the technical foundation and delivery rigor for mission AI solutions:
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End-to-end solution architecture : system boundaries, trust zones, data flows, integrations/APIs, security controls, observability, and cost models.
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Tooling and platform selection : LLMs, embeddings, vector stores, orchestration frameworks, graph technologies, data platforms—documenting tradeoffs and decisions.
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Engineering and delivery standards : secure SDLC, CI/CD quality gates, automated testing, code review practices, evaluation harnesses, and production readiness checklists.
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Hands-on technical leadership : prototypes, reference implementations, PR reviews, mentoring, and architecture governance to ensure delivery quality.
What You Will Need:
- Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse . Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.
- Bachelor’s degree in Engineering, IT, Computer Science, or related field (or equivalent experience).
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Minimum EIGHT (8) years in solutions architecture, software engineering, data engineering, and/or applied ML with a track record of delivering production systems . A Master’s degree may be substituted for up to 2 years of relevant professional experience.
- Strong Python proficiency and strong SQL skills (data modeling, query optimization).
- Experience designing and delivering cloud-based AI/ML solutions end-to-end (ingestion → modeling → deployment → monitoring) in secure environments.
- Hands-on experience with AI application frameworks such as LangChain, Haystack, crewAI , or similar.
- Strong knowledge of core Python ML/data libraries: NumPy, Pandas, Scikit-lear