Aurimas Nausedas
Fractional AI Product Manager & AI Architect. I help enterprise teams ship governed, accountable AI to production — and stop burning cycles on demos that don't survive contact with compliance, finance, or security.
Currently available
Engagements opening for Q3 2026.
Aegis AI is one of the platforms I've architected end-to-end. If you're wrestling with shadow AI, AI cost sprawl, governance gaps, or legacy modernization — I'd love to talk.
Governance
Audit, cost attribution & compliance as first-class concerns
COBOL → Py
Legacy modernization: COBOL, FORTRAN, PL/I, RPG, Assembly
ITIL v4
ITSM copilots on top of existing service desks
RAG
Model selection, retrieval & cost/latency architecture
How I work with teams
Fractional AI Product Manager
Embedded for 2–3 days a week with your AI team. I own roadmap, discovery, stakeholder alignment, and delivery cadence — without the cost of a full-time hire.
- •Define the AI product strategy and roadmap
- •Run discovery with internal users and external customers
- •Translate ML capabilities into shippable product
- •Operate as the bridge between research, eng, design, GTM
Fractional AI Architect
Hands-on design and review for your AI platform. From governance and observability to model selection, RAG architecture, and cost engineering.
- •Reference architecture for governed AI workflows
- •Vendor selection across foundation models, vector stores, MLOps tooling
- •Cost & latency optimization at the request level
- •Security, PII, and compliance design (SOC2, GDPR, HIPAA, EU AI Act)
AI Build Sprints
Fixed-price, fixed-scope sprints to ship one critical AI capability end-to-end — from architecture to a production pilot in 4–8 weeks.
- •Legacy modernization pilots (COBOL/FORTRAN/PL-1 → Python)
- •Governed ITSM copilots on top of existing service desks
- •Internal RAG over governed knowledge bases
- •AI cost & governance retrofits to existing platforms
How I think
Outcome over output
I optimize for measurable business outcomes — cost reduced, cycle time cut, risk eliminated — not for shipped features or model demos.
Governance is a feature, not a bolt-on
Every system I architect treats audit trail, cost attribution, and compliance as first-class concerns. Retrofitting these later is the most expensive mistake in enterprise AI.
Plain English, always
I write artifacts your CFO can read, your legal team can sign off on, and your engineers can implement. No jargon, no hand-waving, no vendor BS.
“Most enterprises don't fail at AI adoption — they fail at AI accountability. The teams that win in this cycle treat governance, cost, and audit as load-bearing product surfaces, not afterthoughts.”
— Aurimas Nausedas, on building Aegis AI
What a good engagement looks like
Great fit
- ✓Series-B to public companies adopting AI
- ✓Regulated industries (finance, healthcare, gov)
- ✓Existing AI investments in need of governance
- ✓Mainframe / legacy modernization mandates
Less great fit
- —Pre-PMF startups looking for an MVP cofounder
- —Vendor wanting a stamp on a marketing piece
- —Teams unwilling to invest in governance
Ready to talk?
Send a short note about what you're building. I'll reply within one business day with a few clarifying questions and (if there's mutual fit) calendar times for a 30-minute exploratory call.