Note: The job is a remote job and is open to candidates in USA. FM Talent Source is an enterprise that provides business and workforce solutions to help organizations nationwide overcome business challenges. They are seeking an AI/ML Solutions Architect to design and deliver secure, scalable, and cost-effective cloud-native AI solutions for federal clients, bridging complex mission needs and modern technology.
Responsibilities
- Design and implement agentic AI systems that enable autonomous decision-making, workflow orchestration, and mission process optimization—with appropriate guardrails and human oversight
- Develop Generative AI applications for summarization, extraction, predictive insights, and conversational interfaces
- 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: 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
- 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: End-to-end solution architecture: system boundaries, trust zones, data flows, integrations/APIs, security controls, observability, and cost models
- Tooling and platform selection: LLMs, embeddings, vector stores, orchestration frameworks, graph technologies, data platforms—documenting tradeoffs and decisions
- Engineering and delivery standards: secure SDLC, CI/CD quality gates, automated testing, code review practices, evaluation harnesses, and production readiness checklists
- Hands-on technical leadership: prototypes, reference implementations, PR reviews, mentoring, and architecture governance to ensure delivery quality
Skills
- 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)
- 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-learn, NLTK, OpenCV
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow
- Experience with search technologies such as Elasticsearch or OpenSearch
- Experience with relational databases (e.g., PostgreSQL, Oracle) and in-memory analytics engines (e.g., DuckDB)
- Experience using cloud SDKs (e.g., Boto3) and building reliable integrations with cloud services
- Familiarity with agentic AI frameworks such as AWS Strands Agents, PydanticAI, and related orchestration patterns
- Advanced prompt engineering skills for complex tasks beyond code generation (reasoning workflows, guardrails, evaluations)
- Experience with asynchronous Python development (asyncio patterns, concurrency, reliability)
- Experience with MCP servers and tool-calling within agentic workflows (tool governance, reliability, and security considerations)
- Experience with Palantir Foundry, Ontology, and AIP
- Strong security-by-design mindset: IAM/least privilege, encryption, secrets management, auditability—and ability to operate within federal compliance constraints
- Excellent communication skills: translate mission needs into architecture decisions, delivery plans, and measurable outcomes
- Experience with 1:N facial recognition search solutions, including secure integration patterns, auditability, governance, and human-in-the-loop workflows
- Knowledge of GPU-accelerated computing (CUDA) and performance optimization for ML inference/training workloads
- AWS Solutions Architect certification
- AWS Certified Generative AI Developer – Professional (or equivalent)
Company Overview