B

Bridgenext

Global digital consultancy for product engineering

AI Technical Lead

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 8 years of experience in software engineering, solution architecture, or technical leadership.
  • Strong software engineering experience with Python, C#/.NET, and/or TypeScript/JavaScript, including APIs, microservices, distributed systems, SQL/NoSQL, event-driven architecture, automated testing, Git, and CI/CD.
  • Strong hands-on experience with Microsoft Azure and enterprise application architecture.
  • Strong understanding of Microsoft Azure architecture, including Azure AI services, AI Search, API Management, App Services, Functions, Containers, Service Bus, Storage, databases, Key Vault, Entra ID, networking, monitoring, and CI/CD.
  • Strong hands-on experience with Azure OpenAI, Microsoft Foundry/Azure AI services, and frameworks such as LangChain/LangGraph, Semantic Kernel, LlamaIndex, or comparable technologies.
  • Demonstrated experience designing and developing Generative AI/LLM solutions, including RAG and agentic AI.
  • Experience taking AI solutions from prototype or proof of concept through production deployment.
  • Experience with MCP, agent/tool integration, and enterprise AI integration.
  • Hands-on experience using AI coding assistants and development agents throughout the software development lifecycle.
  • Strong technical leadership, architecture, problem-solving, mentoring, and client communication skills.
  • A bachelor's or master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related discipline, or equivalent professional experience.
  • Solid written, verbal, and presentation communication skills.
  • Strong team and individual collaboration skills.
  • Ability to maintain composure in varied situations and collaborate effectively.
  • Ability to produce high-quality results with professionalism.
  • Ability to work independently with little supervision or intervention.
  • Flexibility and openness to creative solutions.

Responsibilities

  • Design and deliver enterprise AI solutions using LLMs, RAG, agentic AI, enterprise knowledge retrieval, and intelligent automation.
  • Design prompt and context engineering, structured outputs, tool/function calling, agent orchestration, memory, and human-in-the-loop workflows.
  • Design and implement MCP servers and clients to securely connect AI agents with enterprise applications, APIs, data, and tools.
  • Design secure, scalable, resilient, observable, and cost-effective cloud architectures using appropriate Azure patterns.
  • Use AI-assisted development tools such as GitHub Copilot, Claude Code, OpenAI Codex, or equivalent tools across design, development, testing, debugging, code review, documentation, and modernization.
  • Establish AI evaluation practices covering accuracy, groundedness, relevance, hallucination, retrieval quality, safety, latency, and cost.
  • Implement AI security and guardrails addressing prompt injection, sensitive-data leakage, insecure tool execution, excessive agency, authentication/authorization, role-based access control, and least privilege.
  • Apply Responsible AI, OWASP LLM security guidance, and NIST AI RMF principles as appropriate.
  • Establish observability for model/API performance, token consumption, cost, retrieval quality, agent/tool execution, failures, and AI quality.
  • Provide technical leadership to AI, software, and data engineers; translate architecture into implementable components; and conduct architecture, design, and code reviews.
  • Mentor engineers, establish AI engineering standards and reusable patterns, identify technical risks, and balance rapid experimentation with production engineering quality.
  • Evaluate emerging AI models, frameworks, protocols, coding agents, and open-source or commercial technologies through prototypes and technical assessments.
  • Support client discussions, technical workshops, solutioning, demonstrations, and pre-sales activities.

Desired Qualifications

  • Microsoft Azure Architecture or AI certifications.
  • Experience with enterprise RAG, knowledge architectures, and autonomous or semi-autonomous agents.
  • Experience implementing MCP-based enterprise integrations.
  • Experience with MLOps/LLMOps and AI evaluation/observability platforms.
  • Experience developing reusable AI accelerators, frameworks, or enterprise AI platform capabilities.
  • Consulting or client-facing AI solution delivery experience.

About the Company

Bridgenext

Global digital consultancy for product engineering

Bridgenext is a global digital consultancy that helps organizations reach their digital goals by designing and delivering products, experiences, and solutions that meet real user needs. It operates through cross-border teams in the U.S., Canada, Argentina, and India, offering services in digital product engineering, automation, data engineering, and infrastructure modernization, along with digital experience, creative content, and customer data analytics to elevate brands. The company brings together four brands—Emtec, Emtec Digital, Wave6, and Definition 6—to provide wide-ranging expertise across strategy, engineering, experience design, and analytics. By combining diverse disciplines under one umbrella, Bridgenext differentiates itself with integrated delivery and measurable outcomes. Its goal is to help clients realize tangible digital aspirations through practical, well-coordinated programs that deliver value and measurable results.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Jacksonville, FL
Founded
Not listed

Recently Posted Jobs

Explore more opportunities at Bridgenext

See more jobs