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AI Native Full Stack Engineer - Technical Lead
Employment Type:
Perm
Job Number: 25645
Remote Options: Onsite
Job Description
AI-Native Full Stack Engineer - Technical Lead
Salary Range: $170k to $180k
Job Summary
We are seeking an AI-Native Full Stack Engineer / Technical Lead to drive the design, development, and delivery of modern, AI-powered software systems. This role is highly hands-on and combines full-stack engineering, technical leadership, and AI-native development practices.
The ideal candidate will actively write production code, define system architecture, and lead adoption of agentic development workflows across the engineering team. This position requires experience building and deploying LLM-powered applications, along with a strong foundation in distributed systems and cloud-native development.
Key Responsibilities
Required Qualifications AI / Machine Learning Experience
Leadership & Soft Skills
Preferred Qualifications
Job Summary
We are seeking an AI-Native Full Stack Engineer / Technical Lead to drive the design, development, and delivery of modern, AI-powered software systems. This role is highly hands-on and combines full-stack engineering, technical leadership, and AI-native development practices.
The ideal candidate will actively write production code, define system architecture, and lead adoption of agentic development workflows across the engineering team. This position requires experience building and deploying LLM-powered applications, along with a strong foundation in distributed systems and cloud-native development.
Key Responsibilities
- Design, build, and deploy full-stack applications using modern development frameworks and AI-assisted workflows
- Lead development of LLM-powered features, including prompting, tool/function calling, and streaming outputs
- Architect systems that incorporate agent-based workflows, including planning loops, tool usage, and memory management
- Develop and maintain RAG pipelines, embeddings, and vector database integrations
- Ensure high standards for code quality, testing, observability, security, and performance
- Drive adoption of AI-native engineering practices and improve team productivity through automation and tooling
- Collaborate with cross-functional teams to define technical requirements and deliver scalable solutions
- Mentor engineers through code reviews, pair programming, and technical guidance
- Lead incident response and contribute to continuous improvement through postmortems
- Optimize systems for latency, cost efficiency, and reliability
Required Qualifications AI / Machine Learning Experience
- Hands-on experience building and deploying LLM-based applications in production environments
- Experience with prompt engineering, structured outputs, and tool/function calling
- Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, and vector databases
- Experience designing agentic systems (multi-step execution, planning loops, tool orchestration)
- Familiarity with LLM evaluation techniques, including offline evaluation, datasets, and guardrails
- Knowledge of AI risks such as hallucination, prompt injection, and cost control strategies
- 7+ years of professional software engineering experience (or equivalent hands-on expertise)
- 2+ years of experience in a technical lead or senior engineering role
- Strong proficiency in at least one backend language: C#, .NET, Java, Python, Go, Kotlin, or Node.js
- Experience with RESTful APIs and/or gRPC services
- Frontend development experience using React, Angular, Vue, or Next.js with TypeScript
- Strong database experience with SQL (PostgreSQL, SQL Server, MySQL) and NoSQL systems (e.g., Redis, MongoDB)
- Experience building cloud-native applications on Azure, AWS, or GCP
- Familiarity with containers, orchestration, and Infrastructure as Code (Terraform, Bicep, Pulumi)
- Experience with CI/CD pipelines (GitHub Actions, Azure DevOps)
- Strong understanding of distributed systems, concurrency, and system design principles
Leadership & Soft Skills
- Demonstrated ability to lead through technical contribution and influence
- Strong communication skills with both technical and non-technical stakeholders
- Ability to drive change and improve engineering practices across teams
- Experience mentoring and developing engineers
Preferred Qualifications
- Experience with multi-agent frameworks (e.g., LangGraph, Semantic Kernel, AutoGen)
- Knowledge of event-driven architectures (Kafka, Event Hubs, NATS)
- Experience with model fine-tuning, distillation, or self-hosted inference
- Background in B2B SaaS, procurement, supply chain, or construction technology
- Contributions to open-source projects, technical blogs, or conference speaking engagements
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