[Remote] AI/ML Architect

Note: The job is a remote job and is open to candidates in USA. Take2 Consulting, LLC is seeking an AI/ML Solutions Architect to design and deliver secure, scalable, and cost-effective cloud-native AI solutions for federal clients. The role involves owning end-to-end architectures and leading hands-on implementation, particularly for agentic AI systems and production-grade ML pipelines.

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'
• 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
• 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)
• Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred
• A Master's degree may be substituted for up to 2 years of relevant professional experience

Company Overview