hatch I.T.

AI Engineer

• Implement and maintain LLM and SLM pipelines, including prompt engineering, inference, and evaluation.
• Support RAG pipelines, embeddings, and retrieval systems used in intelligence applications.
• Assist in building agent workflows that automate analytical or operational tasks.
• Write clean, maintainable code (Python or others) to support AI services and integrations.
• Contribute to AI evaluation, testing, and hallucination-mitigation techniques.
• Use AI-assisted development tools (e.g., Copilot, Cursor) to improve development velocity and quality.
• Collaborate with Product and Engineering teams to integrate AI capabilities into user-facing workflows.
• Follow established AI governance, safety, and cost-optimization practices.

Generative AI Engineer, Agentic

Mechanical Engineer

• Own the AI-first user experience for intelligence workflows
• Design and implement workflows where AI meaningfully reduces cognitive load (e.g., investigation setup, triage, summarization, entity linking, report generation, alert review).
• Build “AI-in-the-flow” patterns: inline suggestions, copilots, agent task panels, explainable recommendations, smart defaults, and guided wizards—without turning the product into a chat box.
• Define interaction patterns for agentic experiences (tasking, progress, tool calls, approvals, undo/redo, auditability, and fail-safe fallbacks).
• Conduct lightweight user research (interviews, usability tests, workflow observation) and translate insights into journey maps, task flows, wireframes, prototypes, and shipped UI.
• Partner with Product to clarify user problems, success criteria, and tradeoffs—then execute quickly and iteratively.
• Ensure the UX supports novice-to-expert progression (discoverability for new users, speed and power features for experts).
• Implement designs in a modern front-end stack (typically React + TypeScript), delivering clean, testable, accessible, performant UI.
• Build reusable components and patterns; contribute to (or lead) a design system using tools like Figma + Storybook.
• Instrument experiences with analytics/telemetry to measure adoption, workflow success, and time-to-insight improvements.
• Design for “evidence-first” outputs: citations, sources, confidence indicators, what-changed diffs, and clear user controls.
• Implement guardrails in the UI: policy-aware interactions, redaction/PII-aware patterns (where applicable), and safe failure modes.
• Close the loop with feedback: capture user ratings, corrections, and outcomes to improve models and workflows over time.
• Work daily with Product, AI/ML, and Backend teams to define API contracts, data needs, latency targets, and UX acceptance criteria.
• Raise the bar on craft: advocate for coherent UX, consistent patterns, and high-quality delivery—while keeping momentum and pragmatism.
• Mentor others informally through design critiques, code reviews, and clear communication.

Director of Design Engineering

Proposal Manager

• Lead and manage end-to-end proposal activities including schedule development, kickoff, compliance reviews, color team reviews, production and delivery.
• Orchestrate cross-functional proposal teams including capture managers, solution architects, SMEs, pricing and contracts to ensure timely and high-quality deliverables.
• Analyze RFPs/RFIs/SOWs to develop compliant outlines, content plans, and proposal strategies. Ensure strict adherence to solicitation requirements and internal quality standards.
• Contribute to proposal sections (management, past performance, executive summary, etc) and review drafts for clarity, consistency, and persuasiveness.
• Develop and maintain proposal templates, style guides, and content libraries. Recommend process improvements and tools to enhance proposal operations.
• Serve as a key liaison between internal stakeholders and partners/subcontractors. Facilitate effective communication to maintain alignment and momentum.
• Organize and lead Pink, Red, and Gold Team reviews; consolidate feedback and drive revisions to strengthen proposal quality.
• Support debriefs, lessons learned, and post-proposal assessments to inform continuous improvement.