Senior AI Engineering Lead

CoPilot Innovations (subsidiary of The Plumtree Group) empowers businesses to leverage AI for transformative results. We specialize in custom AI solutions that blend software, automation, and strategy, ensuring technology serves people. We partner with growing brands to implement AI efficiently, delivering impactful results in weeks, not years.

We are looking for a Senior AI Engineering Lead to act as the technical authority across our engineering team — a player-coach who builds deeply on our most demanding accounts while raising the bar for every engineer in the company.

This is a hands-on leadership role, not a pure management role. You will spend roughly half your time shipping production AI systems on 1–2 strategic accounts, and the other half coaching engineers across all accounts, vetting solution architectures, and defining how we use AI tooling (including Claude Code and agentic frameworks) in our software engineering practice.

You will be the person engineers turn to for technical guidance, the reviewer who catches what others miss, and the standards-setter for how CoPilot builds enterprise-ready AI software. The role is designed for someone who is energized by horizontal influence — by making 10 engineers better, not just shipping their own code.

• Build (40–50%) — Architect and ship AI applications across GenAI, Agentic, and ML on 1–2 strategic accounts, including system design, build vs. buy calls, and deploying enterprise-grade pipelines in client cloud environments.
• Vet architecture and AI usage (30–40%, all accounts) — Act as the mandatory technical reviewer at solutioning and pre-build checkpoints, set standards for AI tooling use (Claude Code, agentic workflows), and kill unnecessary complexity.
• Coach engineers (15–20%, all accounts) — Run weekly 1:1s with every engineer, conduct cross-account code reviews with written feedback, and build deliberate growth plans against individual skill gaps.
• Set engineering standards (5–10%, with leadership) — Define AI engineering standards, contribute to hiring and technical interviews, and shape the company's technical direction.

• Strong background in Generative AI/RAG, Agentic AI, Computer Vision, Machine Learning, and AI-driven automation
• Hands-on experience building LLM-driven applications, agentic workflows, and AI microservices, including data ingestion pipelines (batch + streaming) and ETL patterns
• Practical use of tools such as LangChain, LlamaIndex, or alternatives for LLM and multi-agent orchestration
• Strong foundation in classical ML techniques: classification, regression, clustering, ranking, and feature engineering
• Experience with PyTorch and/or TensorFlow for model development and experimentation
• Proficiency with vector databases like MongoDB Atlas Vector Search, FAISS, Pinecone, or similar
• Strong cloud experience: deployment of AI services and workloads on AWS, Azure, or GCP
• Familiarity with cloud AI platforms such as AWS Bedrock, Azure AI Services, GCP Vertex AI
• Hands-on experience with Docker, Kubernetes, and cloud-native deployment patterns
• Experience implementing MLOps/LLMOps: model versioning, CI/CD pipelines (GitLab CI/CD or similar), experiment tracking (MLflow, Kubeflow), LLM evals, and AI observability
• Understanding of cost, latency, performance optimization, and secure, multi-tenant AI deployments
• Strong programming skills in Python, with experience building backend services and APIs
• Working fluency with AI-assisted development tools (Claude Code, Cursor, or equivalent) and a clear point of view on when AI helps vs. hurts engineering output

• Demonstrated experience leading or mentoring teams of 4–8 engineers
• Genuine energy for coaching others — you find it as rewarding as shipping your own work
• Strong stakeholder management and communication skills
• Experience working in consulting or enterprise environments
• Comfortable participating in architecture discussions with client teams
• Ability to explain AI trade-offs to non-technical stakeholders
• Able to hold a standard without becoming a bottleneck — knows when to decide and when to delegate the decision

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field
• 5+ years of hands-on experience in AI/ML engineering, with a focus on Generative AI, RAG, agentic systems, and cloud-based AI
• 2+ years of experience leading or mentoring engineers, with measurable evidence of growing others (not just shipping personally)

• Build High-Impact AI Solutions: Solve real-world problems with sophisticated AI, contributing to projects with direct, tangible impact
• Architect Your Career: Thrive in a fast-paced startup environment with a clear trajectory into broader engineering leadership and dedicated support for professional upskilling
• True Global Flexibility: Fully remote, work-from-anywhere culture with flexible timings that respect your life outside of code
• Premium Compensation: Competitive salaries paid in USD
• Culture of Innovation: A dynamic, ego-free group of experts passionate about building meaningful technology together

If you meet the above qualifications and are excited about the opportunity to build impactful AI solutions while raising the bar for an entire engineering team, we encourage you to apply.