AI Engineer (Go & Python) for LLM-Powered Systems

Location: Lisbon, Portugal / Europe / Remote

Company: ShelterZoom

Department: Product & Engineering

About ShelterZoom

ShelterZoom is a deep tech company and multi-category innovator in cybersecurity, digital content ownership, and business continuity. With nearly 80 patents and trademarks in its portfolio, ShelterZoom is redefining data ownership, tracking, and protection, while advancing cyber resilience with trusted and self-governed AI.

Recognized by Gartner® as a market leader for three consecutive years (2022–2024), ShelterZoom continues to shape the future of digital resilience. From inventing document tokens and Single Source of Truth® (SSOT) technology to building Spare Tire—a life-saving solution for healthcare EHR downtime—and developing safeguards against AI manipulation, ShelterZoom is creating platforms that define the next generation of data ownership, cybersecurity, and artificial intelligence.

Learn more: www.shelterzoom.com

About the Role

We are looking for an AI Engineer with strong Go and Python expertise to build, deploy, and operate production-grade LLM-powered systems.

At ShelterZoom, we bring together high-performing individuals who think creatively, move fast, and push boundaries. If you are ready to unlock new opportunities, create real-world impact, and help shape the future of digital resilience, we’d love to hear from you.

Key Responsibilities:

• Design, build, and maintain production-ready LLM and RAG-based systems with a strong focus on reliability, scalability, and performance
• Architect and implement Retrieval-Augmented Generation (RAG) pipelines, including hybrid search (dense + sparse), re-ranking, and retrieval validation
• Design and manage LLM memory layers, including:
• Short-term memory (context windows)
• Long-term memory (vector databases)
• Structured memory (key-value stores and relational databases)
• Integrate and optimize LLMs, embeddings and chunking (text-embedding-3, BGE, E5, sliding / semantic chunking)
• Develop and orchestrate AI agents, including multi-agent systems (planner–executor, supervisor–worker patterns)
• Implement robust guardrails and hallucination mitigation techniques using revalidation, constraints, and monitoring
• Build observability and evaluation pipelines for LLM systems (quality, latency, cost, and safety)
• Optimize systems for latency, cost efficiency, and throughput, including async inference, streaming, caching, and prompt compression
• Collaborate closely with product, security, and infrastructure teams to deliver secure, enterprise-grade AI solutions
• Contribute to system design, code reviews, testing, and continuous improvement of engineering best practices

Requirements:

• 6+ years of commercial software development experience 
• 3+ years of Go (production) 
• 1+ year of Python (production) 
• English fluent; Russian nice to have
• Working in GMT / GMT +2 timezone, Lisbon based preferred but not mandatory

• Design and implementation of RAG systems, including:
• Hybrid search (dense + sparse)
• Re-ranking strategies
• LLM memory design:
• Short-term (context window)
• Long-term (vector databases)
• Structured memory (KV / relational databases)
• Embeddings & chunking strategies:
• text-embedding-3, BGE, E5
• Sliding window and semantic chunking
• Evaluation frameworks:
• RAGAS, TruLens, DeepEval

• Experience with agent frameworks:
• LangChain, LangGraph
• MCP (Model Context Protocol)
• Multi-agent orchestration patterns
• Prompt engineering:
• System prompts
• Few-shot learning
• Structured outputs

• Guardrails & hallucination mitigation:
• Retrieval validation
• Output constraints
• Observability & monitoring:
• Langfuse, OpenTelemetry, custom tracing
• Cost optimization:
• Token budgeting
• Caching strategies
• Prompt compression
• Latency optimization:
• Async inference
• Parallel calls
• Streaming responses

• Strong proficiency in Python and Go
• Go runtime internals:
• Concurrency model (goroutines, channels)
• Garbage collection
• Core data structures
• Profiling and performance tuning
• Testing practices



• Strong understanding of software design principles:
• SOLID, Clean Architecture, GoF patterns
• Idiomatic Go project layout
• Networking fundamentals:
• TCP/IP and core Internet concepts
• Knowledge Graphs / GraphRAG
• Data systems fundamentals:
• OLTP vs OLAP
• ACID, CAP theorem
• Index structures
• Databases:
• PostgreSQL, MySQL, MongoDB (internal principles and components)
• Infrastructure & DevOps:
• Kubernetes, Prometheus, CI/CD, AWS
• Distributed systems:
• Redis, Elasticsearch, Kafka
• Microservices and high-availability systems
• Exposure to additional technologies beyond the core stack
• Russian language proficiency (nice to have, not required)

Job Details

• Remote Policy: Full Remote
• Contract Type: Full-Time, Contract

Benefits

• Competitive salary
• Learning and development opportunities to support individual growth
• Flexible, remote work with a strong focus on work–life balance and wellbeing
• Open-minded, collaborative, and diverse culture
• Clear career growth path in a company with a one-of-a-kind, category-defining product
• Equal opportunities in a respectful, fair, and socially conscious environment
• A people-first culture built on respect and open communication
• Dynamic and flexible international team
• Opportunity to work on cutting-edge AI-driven cybersecurity and digital resilience platforms with proven market recognition