Senior AI Engineer

About Us

About The Role

Key Responsibilities

• Lead the design and development of AI enabled products from early concept to MVP, customer validation, and early production readiness.
• Translate ambiguous business problems into AI solution designs, experiments, architecture diagrams, evaluation plans, and working systems.
• Design and build LLM based applications using commercial and open source models through APIs, hosted inference, or private deployments.
• Build RAG systems including document ingestion, parsing, chunking, embeddings, vector search, hybrid search, reranking, citation generation, access control, and answer evaluation.
• Build AI agents and tool calling workflows that can use APIs, databases, search, documents, business rules, and human review steps.
• Design orchestration patterns for multi step AI workflows, including planning, tool execution, guardrails, retries, fallback paths, state management, and traceability.
• Build AI evaluation pipelines using golden datasets, test cases, automated checks, human review, quality scoring, regression testing, and failure analysis.
• Evaluate model quality, prompt performance, retrieval accuracy, hallucination rate, latency, cost, reliability, safety, and user experience.
• Design AI systems with human oversight, auditability, traceability, permissions, data privacy, and clear failure handling.
• Work with structured and unstructured data, including PDFs, images, forms, emails, transcripts, logs, knowledge bases, and enterprise records.
• Partner with Senior Full Stack Engineers to integrate AI capabilities into complete products, APIs, dashboards, workflows, and customer facing experiences.
• Build reusable AI components such as prompt templates, agent patterns, evaluation harnesses, model gateways, retrieval services, and reference architectures.
• Identify and manage AI risks including hallucination, prompt injection, data leakage, unsafe outputs, retrieval errors, model drift, cost spikes, and poor user trust.
• Document AI architecture, assumptions, limitations, evaluation results, risk controls, and operational requirements.
• Stay close to AI industry developments and convert relevant ideas into practical product opportunities for VentureOne.
• Contribute to hiring, technical assessment, mentoring, and AI capability building for the Foundry team.

Minimum Qualifications

• Strong experience building applied AI products, LLM based applications, AI platforms, or machine learning systems.
• Proven ability to lead technical direction for AI systems in complex and ambiguous environments.
• Hands on experience with LLMs, prompt design, embeddings, vector databases, RAG, model APIs, structured outputs, and AI orchestration.
• Experience building AI agents, tool calling workflows, function calling, workflow automation, or AI powered business processes.
• Strong programming experience in Python and strong understanding of production software engineering practices.
• Experience with AI frameworks and libraries such as LangChain, LlamaIndex, Semantic Kernel, Haystack, AutoGen, CrewAI, Flowise, or similar tools.
• Experience with vector stores and search systems such as pgvector, Pinecone, Weaviate, Qdrant, Elasticsearch, OpenSearch, Azure AI Search, or similar platforms.
• Experience designing ingestion pipelines for documents, text, tables, metadata, permissions, and enterprise knowledge sources.
• Experience evaluating AI systems using structured test sets, quality metrics, automated evaluation, human review, benchmark based approaches, or production feedback loops.
• Good understanding of APIs, back end services, data pipelines, cloud deployment, observability, logging, tracing, and system integration.
• Strong understanding of AI safety, responsible AI, privacy, security, prompt injection defense, data leakage prevention, and operational failure modes.
• Ability to optimize AI systems for cost, latency, quality, reliability, and scalability.
• Ability to move quickly from idea to prototype while maintaining clear thinking about evaluation and production readiness.
• Strong communication skills with the ability to explain AI behavior, limitations, risks, and tradeoffs to technical and non technical stakeholders.

Preferred Qualifications

• Experience with agentic systems, AI workflow builders, orchestration platforms, multi agent systems, or AI control planes.
• Experience with cloud AI services on AWS, Azure, GCP, or private cloud environments.
• Experience with model gateways, model routing, prompt versioning, prompt registries, experiment tracking, and AI observability.
• Experience with document intelligence, OCR, form extraction, classification, summarization, entity extraction, and knowledge graph enrichment.
• Experience with AI governance, audit trails, human oversight, model evaluation, policy controls, and responsible AI frameworks.
• Experience in regulated domains such as government, fintech, identity, real estate, health, or enterprise platforms.
• Experience building customer facing AI products, not only research prototypes.
• Experience creating reusable AI patterns, reusable prompts, agent templates, evaluation frameworks, and reference architectures.
• Experience deploying AI capabilities with security, tenant isolation, role based access, cost monitoring, and production monitoring.
• We provide a competitive, tax-free salary and a comprehensive benefits package in a collaborative, innovative and inclusive work environment.
• Our benefits include an education allowance, free on-site meals, annual flight allowance, health coverage, relocation support (if applicable), and access to well-being activities such as sports and recreational events.Join us to drive innovation and shape the future of technology!

How To Apply