WE ARE LOOKING FOR
AVANCEESoftware is seeking a Senior AI Engineer to lead the design, development, and deployment of advanced AI solutions across two high-impact tracks: accelerating our internal development pipeline with AI-powered tooling, and embedding intelligent capabilities directly into our IoT and software products.
On the engineering side, you will drive the adoption of agentic coding workflows, AI-assisted code review and testing, and intelligent automation across our CI/CD pipeline - measurably increasing the speed and quality with which our engineering teams deliver software.
On the product side, you will architect and build AI features that our customers interact with directly: natural language interfaces, predictive analytics, intelligent automation, and LLM-powered reasoning layers integrated into our platform's IoT and cloud stack.
This is a high-ownership role for someone who combines deep technical expertise with a builder's mindset - someone who can move from research to production, mentor a team, and thrive at the intersection of AI engineering and product impact.
YOU WILL BE WORKING ON
AI for the Software Development Pipeline
• Architect and operationalize agentic, AI-driven development workflows that automate the end-to-end software lifecycle-from design and coding to testing and deployment.
• Build AI-assisted code review, automated testing generation, and documentation to reduce manual overhead across engineering.
• Develop intelligent CI/CD automation: automated test triage, failure analysis, deployment risk scoring, and release quality gates.
• Create and maintain MCP servers and tool integrations that connect LLMs to internal developer systems (GitHub Enterprise, JetBrains TeamCity, etc.).
• Establish evaluation frameworks and guardrails to ensure AI-generated code meets security, quality, and architecture standards.
AI Features in Products
• Architect and lead end-to-end delivery of AI features embedded in AVANCEESoftware IoT and software platform.
• Design and implement RAG pipelines, vector databases, and semantic search to power intelligent product experiences.
• Build natural language interfaces and conversational features using LLM APIs (Anthropic Claude, OpenAI) integrated with our backend services (Quarkus, Kafka, MQTT).
• Develop predictive analytics and anomaly detection capabilities over IoT time-series data (TimescaleDB, PostgreSQL, Neo4j).
• Design AI orchestration layers connecting cloud intelligence with edge inference on embedded targets (Zephyr, FreeRTOS, Nordic/Espressif MCUs).
Technical Leadership & Architecture
• Lead technical design reviews, code reviews, and architecture decisions for all AI components.
• Mentor junior and mid-level engineers, establishing best practices for prompt engineering, model evaluation, and production-grade AI reliability.
• Partner with product and platform teams to translate business requirements into AI-driven solutions with measurable outcomes.
• Evaluate and adopt emerging AI frameworks and tooling, contributing to our AI roadmap.
• Ensure all AI systems meet security, data privacy, and compliance requirements; maintain observability and audit trails.
REQUIRED QUALIFICATIONS
Required
• 6+ years of professional experience in software engineering, with at least 3+ years focused on AI/ML systems in production.
• Strong hands-on expertise with LLMs and GenAI frameworks (LangChain, LlamaIndex, or similar) and vector databases.
• Demonstrated experience building AI-powered developer tooling or automating software engineering workflows with LLMs.
• Experience designing and deploying RAG pipelines, agentic systems, and multi-agent workflows at production scale.
• Proficiency in Python; familiarity with integrating AI features across the full-stack.
• Solid understanding of MLOps practices: model lifecycle management, monitoring, evaluation, and CI/CD for AI systems.
• Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker/Kubernetes).
• Strong software engineering fundamentals: testing, code review, documentation, and version control (Git).
• Excellent communication skills - able to convey complex AI concepts clearly to both technical and non-technical stakeholders.
• Degree in Computer Science, Artificial Intelligence, Engineering, Mathematics, or equivalent practical experience.
Nice to Have
• Hands-on experience with Anthropic Claude API, OpenAI API, n8n, or similar orchestration and automation tools.
• Familiarity with agentic coding tools such as Cursor or Claude Code within team engineering.
• Knowledge of IoT systems, MQTT, Kafka, embedded AI, or edge inference (Zephyr, FreeRTOS, Nordic/Espressif).
• Experience with graph databases (Neo4j) or time-series databases (TimescaleDB) for AI feature development.
• Background in a product-focused startup or scale-up environment where AI was a core business differentiator.