Four roles, all central to how Nefotir actually delivers — not support functions bolted onto a product that already exists.
Lead AI Engineer — Agentic Harness Expertise
Nefotir's entire delivery model runs on a six-agent pipeline — Extraction, Documentation, Risk Scoring, Mapping, Validation, and Generation — working together on every legacy modernization engagement. This role owns the harness that pipeline runs on: the orchestration, tool-calling, memory, guardrails, and observability layer every other agent and engineer builds against.
Responsibilities
- Architect and build the agent harness: tool use, memory, guardrails, retries, and observability
- Design and maintain the orchestration layer connecting Nefotir's six-agent pipeline
- Set engineering standards for agent reliability and failure handling across engagements
- Work embedded, directly inside client environments alongside their engineers
- Mentor other engineers on agent design patterns as the team grows
What We're Looking For
- Hands-on experience building production agent systems or harnesses (LangGraph, LangChain, or a comparable custom orchestration layer)
- Strong Python and systems-design fundamentals
- Real experience with LLM tool-calling, structured outputs, and guardrail/evaluation design
- Comfortable working directly inside unfamiliar, sometimes legacy, client codebases
- Startup mindset — comfortable with ambiguity and full ownership
Nice to Have
- Exposure to SAP, MuleSoft, or Oracle integration platforms
- Prior forward-deployed or embedded-engineer experience
- Open-source contributions to agent frameworks
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AI Strategist with Product Manager Instincts
Every engagement starts with Assess — the first step of Nefotir's Assess, Map, Migrate playbook. This role owns that step: translating a client's messy legacy-modernization problem into a scoped, sequenced plan our engineers and agents can actually execute against.
Responsibilities
- Run discovery and assessment engagements with clients — interviews, systems review, scoping
- Translate technical and business constraints into a prioritized, sequenced roadmap
- Partner with engineering to scope what's automatable versus what needs custom work
- Own client-facing materials that distill complex modernization plans into clear decisions
- Bring the voice of the client back into how the accelerator and playbook evolve
What We're Looking For
- Product management or technical-strategy background at a software or consulting company
- Equally comfortable in a room with engineers and with executives
- Strong written communication — scoping docs and roadmaps people actually act on
- Genuine curiosity about agentic AI systems, even without an engineering background
Nice to Have
- Exposure to enterprise software, ERP, or systems-integration domains
- Background in management consulting or technical PM roles
- Experience scoping legacy modernization engagements specifically
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Senior AI Engineer — Open LLM Evaluation Expertise
Model choice directly determines what's economically viable for a client engagement — token costs and quality tradeoffs shape everything downstream. This role owns how Nefotir evaluates and selects models, open-weight and proprietary alike, across every engagement.
Responsibilities
- Build and maintain evaluation pipelines and benchmarks across Nefotir's use cases — extraction, mapping, code generation, risk scoring
- Own model selection recommendations, balancing cost, latency, and quality
- Track the open-model landscape and evaluate fit for client environments and constraints
- Work with the Generation and Validation agents to tune prompting and fine-tuning where it earns its cost
What We're Looking For
- Hands-on experience running LLM evaluations — benchmark design, human-in-the-loop eval, automated scoring
- Familiarity with open-weight model ecosystems and self-hosting/inference tradeoffs
- Strong Python and ML engineering fundamentals
- Working understanding of token economics and cost/quality tradeoffs at scale
Nice to Have
- Experience with vLLM, Ollama, or similar inference-serving stacks
- Published evals or benchmark work
- Fine-tuning experience on open-weight models
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Senior AI Security Engineer
Nefotir's agents run inside client environments with access to legacy systems and sensitive data — that access only works if it's trustworthy. This role owns AI governance and security across every engagement, closely tied to the Risk Scoring Agent and Nefotir's AI Governance service line.
Responsibilities
- Define and implement security guardrails for agents operating inside client environments — data access, prompt injection defense, output validation
- Own the Risk Scoring Agent's compliance and complexity-flagging logic
- Build AI governance frameworks clients can adopt — shadow-AI risk, token/compute spend controls
- Partner directly with client security and compliance teams during engagements
- Stay current on AI-specific security threats — prompt injection, data exfiltration, model risk
What We're Looking For
- Security engineering background with specific AI/LLM security experience
- Solid understanding of prompt injection, agent sandboxing, and data governance
- Comfortable operating inside enterprise client environments with strict compliance requirements
- Strong communicator — able to explain AI risk clearly to non-technical stakeholders
Nice to Have
- Prior enterprise security or compliance-adjacent role (SOC 2, financial services, insurance)
- Experience with AI governance frameworks such as the NIST AI RMF
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