Principal AI Engineer

🕒 May 15

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Sigma Software Group

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2002

🎮 Gaming

📡 Telecommunications

Software Development • Gaming • Telecommunications

Sigma Software Group is a multinational company, established in 2002, that specializes in providing high-quality software development, graphic design, testing, and support services. The company focuses on delivering solutions across various industries such as automotive, telecommunications, aviation, advertising, gaming, banking, real estate, and healthcare. Sigma Software values professional growth, offers remote work opportunities worldwide, and caters to world-renowned clients like AstraZeneca, Scania, and SAS. The company emphasizes a culture of continuous education, mentorship, and flexible work environments, making it a preferred workplace for IT specialists aiming to work on complex solutions utilizing cutting-edge technologies. Sigma Software is committed to innovative solutions and engineering the future while also contributing to social causes such as charitable work in Ukraine.

📋 Description

• Consult clients during presales to assess AI readiness, constraints, and success criteria, translating visions into actionable requirements • Prepare and present presales deliverables including architecture diagrams, assumptions, risks, estimates, scalability considerations, and implementation roadmaps • Define AI use cases and agentic scenarios based on client needs • Select and justify LLMs per use case based on requirements, cost, latency, safety, capability • Architect multi-agent frameworks with orchestrator agents and MCP-style protocols • Design and implement single-agent/multi-agent AI systems with defined roles, tool access, memory, safety boundaries • Build orchestration logic (routing, delegation, retries, fallback strategies, consensus, human-in-the-loop flows) • Develop RAG pipelines (data ingestion, chunking, embeddings, vector databases, hybrid retrieval, relevance optimization) • Implement learning & feedback loops for continuous agent improvement • Design custom or adapted models (prompt-tuned agents, LoRA fine-tuning, domain-inherited models)

🎯 Requirements

• 5+ years in AI engineering or related roles • Designing and building AI-powered systems in production • Agentic frameworks, multi-agent collaboration, orchestrator/worker models • RAG pipelines, relevance tuning • Python and/or TypeScript, API design, microservices, cloud-native architectures • Practical knowledge of multiple LLM providers (OpenAI, Anthropic, open-source) • Ability to build/adapt models (prompt-tuned agents, LoRA fine-tuning, inheritance from foundation models) • Knowledge of AWS Bedrock, Azure OpenAI, GCP Vertex AI • Understanding governance, security, data residency, pricing models, enterprise integration for cloud AI platforms • Production-grade mindset: observability, logging, security, PII handling, cost-efficiency • Strong communication skills for explaining AI concepts to non-technical stakeholders • English level: Upper-Intermediate

🏖️ Benefits

• Flexible hybrid/remote work option