Lead AI Engineer - Generative AI & Agentic AI: Cogentiq

It's fun to work in a company where people truly BELIEVE in what they are doing!

• We're committed to bringing passion and customer focus to the business.*

### **Role Overview:**

We are looking for an accomplished **Lead AI Engineer** to design, build and productionize next\-generation AI solutions across enterprise use cases. This is a highly hands\-on role at the intersection of **Generative AI, Agentic AI, software engineering and AI architecture**.

The ideal candidate brings strong engineering foundations and has successfully taken GenAI solutions beyond experimentation and PoCs into **scalable, secure and production\-grade enterprise systems**.

### **What You'll Do**

• Architect, develop and productionize enterprise\-scale **Generative AI and AI/ML solutions**.
• Design sophisticated **LLM\-powered applications** using RAG, AI agents, tool/function calling, orchestration and multi\-agent workflows.
• Build GenAI solutions leveraging frameworks such as **LangGraph, LangChain, Semantic Kernel** or equivalent.
• Design scalable AI services, backend applications and APIs using **Python** and modern engineering frameworks.
• Build solutions leveraging **LLMs, embeddings, vector databases, knowledge graphs and semantic/knowledge layers**.
• Integrate AI capabilities with **Snowflake**, enterprise data platforms, business applications, APIs and cloud ecosystems.
• Establish robust AI engineering practices covering **LLM evaluation, observability, guardrails, security, latency, reliability and cost optimization**.
• Design end\-to\-end AI/ML pipelines spanning experimentation, deployment, monitoring and continuous improvement.
• Evaluate emerging LLMs, agentic frameworks and AI technologies and translate them into practical enterprise solutions.
• Drive technical design and architecture decisions for AI platforms and products.
• Collaborate with product managers, data scientists, architects and business stakeholders to translate complex requirements into scalable AI solutions.
• Provide technical leadership, mentor engineers and establish strong engineering practices across the team.

### **What We're Looking For**

• **10\+ years of overall experience** in software engineering, AI/ML, data or related technology roles, with significant recent experience building AI/GenAI solutions.
• Strong hands\-on expertise in **Python** with excellent software engineering and system\-design fundamentals.
• Proven experience designing, building and deploying **LLM/Generative AI applications in production**, rather than only PoCs or experimentation.
• Deep hands\-on understanding of **RAG, prompt engineering, embeddings, vector search, LLM orchestration and Agentic AI**.
• Experience building **AI agents,** **tool/function\-calling** **workflows and multi\-agent systems**.
• Hands\-on experience with one or more LLM ecosystems such as **OpenAI, Azure OpenAI, Anthropic Claude or Google Gemini**.
• Strong understanding of **REST APIs, microservices, distributed systems, databases and enterprise application architecture**.
• Experience with **Snowflake** and modern enterprise data ecosystems.
• Strong experience with at least one major cloud platform: **AWS, Azure or GCP**.
• Experience implementing **LLM evaluation, monitoring, observability, security, responsible AI and guardrails**.
• Ability to independently lead the technical design and implementation of sophisticated AI solutions.
• Strong problem\-solving, stakeholder communication and technical leadership capabilities.

### **Good to Have**

• Experience with **knowledge graphs, ontologies, semantic layers or GraphRAG**.
• Hands\-on exposure to **MLOps/LLMOps, model serving, CI/CD and AI observability platforms**.
• Experience with vector databases such as **Pinecone, Weaviate, Milvus, pgvector or Redis**.
• Experience with **fine\-tuning, model adaptation and open\-source LLMs**.
• Experience with **AI security, governance, privacy and enterprise AI architecture**.
• Hands\-on experience with frameworks/tools such as **PyTorch, Hugging Face, LangGraph, LangChain or Semantic Kernel**.
• Understanding of **data engineering, distributed data processing, streaming architectures and modern data platforms**.
• Experience with **Snowflake Cortex, Cortex Search, Cortex Agents** or related Snowflake AI capabilities.
• Prior experience mentoring senior engineers or technically leading engineering teams.

### **Education**

• Bachelor’s or Master’s degree in **Computer Science, Engineering, Artificial Intelligence, Data Science or a related** **quantitative/technical** **discipline**.
• Strong academic background, preferably from a **premier** **engineering/technology** **institution** with a demonstrated record of academic and technical excellence.

### **What Will Make You Stand Out**

We are particularly interested in engineers who can demonstrate that they have **personally architected and built production GenAI systems**, rather than simply experimented with LLMs.

Strong candidates will be able to discuss real\-world experience around:

• Production **RAG and Agentic AI architectures**
• Building scalable **Python/API\-based AI services**
• LLM evaluation and observability
• Enterprise data and application integration
• Security and guardrails
• Latency and inference\-cost optimization
• Taking an AI solution from **prototype production scale**

If you like wild growth and working with happy, enthusiastic over\-achievers, you'll enjoy your career with us!

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