Senior Software Engineer - Full Stack (React/Node.js)

We are building a portfolio of agentic operations — production‑grade AI agents that plan, act, and continuously improve the everyday experiences of our employees.

As Executive Director, Software Engineer , you will own the end‑to‑end technical direction and hands‑on architecture of the Digital Employee Experience and the flagship agents built on it.

This is a hands‑on senior engineering leadership role: you will write code, design systems, run production, and set the technical bar — while coaching a team of engineers across squads.

Job responsibilities

- Own the reference architecture for agentic operations: orchestration, planning, tool‑use, memory, retrieval (RAG / GraphRAG), evaluation, guardrails, observability, human‑in‑the‑loop, cost governance, and lifecycle (build → evaluate → deploy → monitor → retire).
- Choose and evolve the stack (agent frameworks, model gateway, vector stores, feature/knowledge stores, workflow/queue, telemetry, red‑team & eval harness). Balance make‑vs‑buy against firm standards and controls.
- Define the golden path so any employee‑experience squad can ship a safe, evaluated agent in weeks — not quarters.

Flagship employee‑experience agents

- Ship agents that measurably deflect / auto‑resolve high‑volume employee journeys, IT service desk incidents, access & entitlements.
- Design multi‑agent and human‑in‑the‑loop patterns that know when to act, when to draft, and when to escape.
- Instrument every agent with business KPIs (deflection rate, time‑to‑resolve, CSAT, cost per interaction) and quality KPIs.

Reliability, safety, and controls

- Establish SRE for agents: SLOs, error budgets, canaries,



circuit breakers, prompt/model version pinning, deterministic replay, rollback.
- Partner with cybersecurity, privacy, model risk, controls, and audit to make responsible AI concrete: data minimization, purpose limitation, PII handling, evaluation before change, model & prompt inventory, drift detection, red‑teaming, jailbreak defense, secret and tool‑use hygiene.
- Own the evaluation harness: offline benchmarks, online A/B, gold sets, LLM‑as‑judge with human calibration, regression gates in CI/CD.

Delivery leadership

- Lead squads via principal/lead engineers; set the technical bar via architecture reviews, code quality standards, and design docs.
- Grow senior Italent (staff / principal); run a strong hiring bar; sponsor diverse talent.

Business partnership

- Communicate crisply to Managing Directors and executive stakeholders — trade‑offs, risks, timelines, and results.

Required qualifications, capabilities and skills

- 12+ years of software engineering experience, including 5+ years leading engineers and 3+ years shipping production ML/AI (with at least 1+ year shipping LLM‑ or agent‑based systems to real users).
- Deep hands‑on expertise in at least one modern language (Python, TypeScript, Java, Go) and comfort operating polyglot codebases.




- Track record of designing and running large‑scale distributed systems in production (SLOs, on‑call, incident command, cost).
- Practical experience with the agentic stack: LLM orchestration (. LangGraph, LlamaIndex, Semantic Kernel, custom), tool/function calling, RAG, evaluation harnesses, guardrails, prompt & model versioning, model gateways. Hands‑on with Model Context Protocol (MCP) architectures — designing servers/clients, tool schemas, capability negotiation, and secure enterprise deployment patterns.
- Strong grounding in data platforms (Databricks / Snowflake / lakehouse patterns), event streaming, and modern MLOps/LLMOps (CI/CD, feature/prompt/model registry, observability).
- Proven leadership in responsible AI, security, and controls for enterprise deployments: PII/PCI/PHI handling, model risk, red‑teaming, jailbreak & prompt‑injection defense, secret & tool‑use hygiene.
- Executive‑level communication: you can move fluently between a whiteboard architecture, a code review, and a conversation with a Managing Director.
- Bachelor's in Computer Science or related discipline, or equivalent industry experience.

Preferred qualifications, capabilities and skills

- Experience building employee‑facing products at scale (IT service desk, HR tech, knowledge management, workplace assistants).
- Experience integrating with different data sources, ServiceNow, identity providers, endpoint management, and enterprise search.
- Experience with multi‑agent patterns (planner‑executor, supervisor‑worker, debate/critique) and long‑horizon workflows.
- Contributions to open source, published research, patents, or public talks in AI/agents/SRE.
- Prior experience in

📌 Remote Senior Software Engineer: Ai-Native Code Review (Juan José Castelli)
🏢 Outlier
📍 Juan José Castelli