Senior Engineer, Agentic System

ECCO Select is a talent acquisition and consulting company specializing in people, process and technology solutions. We provide the talent behind the technology enabling our clients to achieve their goals. For more information about ECCO Select, visit us at .

Position Title: Senior Engineer, Agentic Systems

Location Information

Remote

Position Responsibilities:

As a Senior Engineer, Agentic Systems, you will play a central role on a small, highly agile engineering team, enjoying high autonomy and ownership of end-to-end product development. This role is well-suited for engineers who thrive in environments with minimal oversight and where shipping real systems rapidly—from asking the right questions to delivering production-ready code—is key.

Core responsibilities include:

• Product Engineering: Collaborate directly with stakeholders to understand vague requests, deduce real needs, and design & ship robust systems without waiting for fully-specified product specs.
• Agentic Systems Engineering: Build, deploy, and productionize LLM-driven workflows, continuously monitoring and hardening them for real-world use.
• System Design: Architect and develop across the stack—front end, back end, real-time/streaming components, databases, and APIs with an eye on scalability, reliability, and maintainability.
• AI-Augmented Engineering: Leverage modern AI coding workflows and coding assistants (e.g., Claude Code, Cursor, Copilot) to maximize efficiency and output, while maintaining critical review and quality checks.
• Agentic LLM System Design: Apply concepts such as agent patterns, tool/function calling, Retrieval-Augmented Generation (RAG), prompt engineering, output structuring, guardrails, evals, tracing/observability, and more.
• Stakeholder and Product Collaboration: Engage confidently with technical and non-technical stakeholders alike, translating fuzzy asks into actionable development items, and navigating requirements changes with a proactive approach.
• AI Adoption Support: Deliver targeted enablement sessions to help teams organization-wide maximize the value of AI tools, advise leadership on adoption strategies, flag risk factors, and help create policy around best practices and responsible AI use.
• Documentation & Enablement: Develop runbooks, internal docs, and practical user guides for internal tools and processes. Bridge the technical–non-technical gap by articulating what systems can and can''t do, especially in failure scenarios.

Essential Skills, Experience

• End-to-End Product Engineering: Experience designing, building, and shipping complex products with minimal guidance; autonomy in translating ambiguous asks into delivered features.
• Agentic LLM Systems: Proficiency with LangGraph or LangChain, prompt engineering, tool/function calling, system guardrails, evaluation frameworks, observability, and related concepts for LLM-driven workflows.
• RAG System Expertise: Practical hands-on experience with RAG pipelines (chunking, embedding model selection, hybrid search, reranking, retrieval evaluation) and relevant vector DBs (ChromaDB, Pinecone, Typesense, pgvector, Weaviate, FAISS).
• Full-Stack Development:
• Back End: Advanced Python (FastAPI, Flask, Django, Pydantic), solid grounding in OOP, functional patterns, concurrency (asyncio, threading), virtual environments, testing frameworks (pytest, unittest).
• Front End: React, TypeScript, SCSS, modern build tools (Vite, Webpack), in-depth with custom hooks, context/state management, routing, component lifecycle, and performance optimization.
• Architectural Fluency: Deep familiarity with common architectural patterns (MVC, layered/clean architecture, event-driven design), and the ability to justify application in different scenarios.
• Real-Time System Design: Experience with SSE, WebSockets, streaming responses, job queues, and scalable background worker design.
• API Mastery: REST and GraphQL design, evolution-resilient internal/external API contracts.
• Database Proficiency: PostgreSQL, MySQL/MariaDB, NoSQL, vector datastores—versed in strengths, trade-offs, and appropriate use cases.
• Caching & Performance: Redis, edge and query-layer caching strategies, and cache invalidation patterns.
• Scaling and Optimization: Load & scale testing, data modeling for performance, traffic analysis.
• Security and Auth: JWT/OAuth flows, auth middleware, and experience with tools like Auth.js, Firebase Auth, Supabase Auth, and SSO providers.
• DevOps: GitHub Actions, CI/CD pipelines, YAML, infrastructure as code/config.
• Server/Infrastructure: AWS, Nginx/Apache, Gunicorn, Ubuntu, Bash; bonus for Kubernetes (deployments, services, basic Helm) and debugging containerized environments.
• Modern AI Coding Workflows: Enthusiastic adopter of AI coding assistants and aware of trade-offs, extensive usage, and effective orchestration of these tools as part of the engineering process.
• Stakeholder Engagement: Skilled in discovery conversations with non-technical users, able to navigate ambiguous asks and surface root needs. Decisive when architectural choices aren''t fully prescripted, comfortable pushing back or clarifying direction as needed.
• Communication: Clarity in communicating trade-offs, risks, and realistic timelines to both technical and non-technical audiences.

• Secondary and Nice to Haves: PHP (server-side APIs, OOP, namespacing, Composer, modern PHP syntax)
• NodeJS (AdonisJS or comparable frameworks)
• Kubernetes and container orchestration (Helm, configmaps/secrets, debugging)
• ML/algorithmic skills (classical ML concepts, Python ML stack, model evaluation)—though primary ML expertise is covered by an SME
• React Native (for mobile platforms)

• Personal Attributes: Relishes autonomy—takes initiative to own problems end-to-end and deliver without regular hand-holding
• Optimizes for shipping the right solution quickly rather than striving for an elusive perfect architecture
• Pushes back with reasoned alternatives when technical asks are misaligned with broader goals
• Comfortable in healthy, supportive, low-burnout work cultures; does not seek or reward burnout-level commitment

Qualifications:

• ~5+ years experience as a product engineer or full-stack engineer, ideally with direct exposure to agentic LLM systems in production.
• Demonstrable experience delivering full product cycles—requirements through production — in environments with minimal supervision.
• Expertise in Python and React/TypeScript stack with associated tooling and frameworks.
• History of adopting and championing AI-powered development workflows.
• Education- Technical Bachelors or higher

ECCO Select is committed to hiring and retaining a diverse workforce. Our policy is to provide equal opportunity to all people without regard to race, color, religion, national origin, ancestry, marital status, veteran status, age, disability, pregnancy, genetic information, citizenship status, sex, sexual orientation, gender identity or any other legally protected category. Veterans of our United States Uniformed Services are specifically encouraged to apply for ECCO Select opportunities.