Experience:

• 2–4 years of professional experience with a backend focus and solid full-stack instincts

Responsibilities:

• Design, build & maintain scalable backend services and APIs for GenAI features
• Develop GenAI applications end-to-end from prototype through production
• Orchestrate agentic workflows using frameworks like CrewAI, Autogen, or LangGraph
• Implement retrieval and memory patterns backed by vector and graph stores
• Own quality in production including observability, cost and latency optimization, evaluation frameworks, and safety guardrails
• Collaborate cross-functionally with design, frontend, and product teams to shape the GenAI roadmap
• Partner with internal business owners to understand workflows and translate requirements into GenAI solutions
• Improve sales efficiency and business processes by delivering agentic workflows tailored to GTM stakeholder needs

Additional responsibilities:

• Engage with non-technical business owners to grasp workflows and convert them into technical solutions
• Measure success in terms of sales efficiency, process improvement, and stakeholder outcomes
• Work alongside experienced engineers and product leaders gaining exposure to cutting-edge GenAI technologies
• Operate with startup agility inside a global SaaS company with high ownership and fast execution
• Join a collaborative, low-ego engineering culture valuing craftsmanship, curiosity, and impact

Nice to have:

• Experience with LangSmith, Langfuse, Weights & Biases, prompt management systems, and evaluation frameworks
• Experience with vector and graph databases such as pgvector, Pinecone, Weaviate, Neo4j
• Deep understanding of retrieval optimization, hybrid search, and context-window management
• Experience hosting and serving open-source models alongside commercial APIs like OpenAI and Anthropic
• Familiarity with embeddings pipelines, AI safety tooling, and guardrail frameworks
• Experience building products from 0 to 1
• Strong product intuition and customer-centric thinking

More skills:

Python, Node.js, TypeScript, REST, GraphQL, SQL, graph databases, AI Evaluation Frameworks, Postgres, MySQL, MongoDB, Redis, Memcached, Kafka, Nginx, Docker, React, CI/CD, testing, debugging complex distributed systems

Other:

• Work on production-grade AI systems that solve meaningful customer problems
• Redefine experimentation and optimization through AI
• See your work reach customers quickly
• Growth and learning opportunities in real-world AI deployment challenges