Senior AI Engineer

About VentureOne

About the Role

Key Responsibilities

• Lead AI-enabled products from concept through MVP, customer validation, and early production readiness.
• Translate ambiguous business problems into solution designs, experiments, architecture diagrams, evaluation plans, and working systems.
• Build LLM applications, RAG systems, AI agents, multi-step workflows, and evaluation pipelines.
• Evaluate quality, retrieval accuracy, hallucinations, latency, cost, reliability, safety, and user experience.
• Design systems with oversight, auditability, traceability, permissions, privacy, and failure handling.
• Integrate AI capabilities into products, APIs, dashboards, workflows, and customer-facing experiences.
• Build reusable AI components and manage risks such as prompt injection, data leakage, model drift, and unsafe outputs.
• Document architecture, limitations, evaluation results, risk controls, and operational requirements.
• Contribute to hiring, technical assessment, mentoring, and AI capability building.

Minimum Qualifications

• Strong experience building applied AI products, LLM applications, AI platforms, or machine learning systems.
• Proven ability to lead technical direction in complex and ambiguous environments.
• Hands-on experience with LLMs, prompt design, embeddings, vector databases, RAG, model APIs, structured outputs, and orchestration.
• Experience building AI agents, tool-calling workflows, function-calling systems, or AI-powered business processes.
• Strong Python programming and production software engineering experience.
• Experience with AI frameworks, vector stores, search systems, document ingestion, and enterprise knowledge sources.
• Experience evaluating AI systems with structured tests, quality metrics, automated evaluation, human review, benchmarks, or production feedback.
• Understanding of APIs, backend services, data pipelines, cloud deployment, observability, logging, tracing, and system integration.
• Understanding of AI safety, responsible AI, privacy, security, prompt injection defense, data leakage prevention, and operational failures.
• Ability to optimize AI systems for cost, latency, quality, reliability, and scalability.
• Ability to move quickly from idea to prototype while maintaining evaluation and production readiness.
• Strong communication skills for explaining AI behavior, limitations, risks, and tradeoffs.

Preferred Qualifications

• Experience with agentic systems, workflow builders, orchestration platforms, multi-agent systems, or AI control planes.
• Experience with AWS, Azure, GCP, or private cloud AI services.
• Experience with model gateways, routing, prompt versioning, experiment tracking, and AI observability.
• Experience with document intelligence, OCR, extraction, classification, summarization, entity extraction, or knowledge graphs.
• Experience with AI governance, audit trails, human oversight, policy controls, or responsible AI frameworks.
• Experience in regulated domains or building customer-facing AI products and reusable AI patterns.
• Experience deploying AI with security, tenant isolation, role-based access, cost monitoring, and production monitoring.

Benefits

• The company provides a competitive tax-free salary and comprehensive benefits package.
• Benefits include an education allowance, on-site meals, annual flight allowance, health coverage, relocation support when applicable, and well-being activities.