At Bridgenext, we engineer Growth Operating Systems. Most enterprises have spent millions on their revenue stack and still aren't seeing the growth they expected.They have tools that function, but no system that wins. We help growth-hungry companies close that gap by turning fragmented platforms, siloed teams, and disconnected data into one integrated Growth OS. More than a technology company or marketing agency, we're a global digital consultancy with experts in engineering, data, AI, creative and more.

Our teams are made up of experts who believe in engineering impact, starting with putting people at the center of everything we do. Every team member directly shapes our work, culture, and values. Nothing matters more to us than a kind, respectful, fulfilling environment that supports everyone. Our flexible, inclusive culture gives you the autonomy, resources, and opportunities to thrive.

The AI Technical Lead is a hands-on technical leadership role responsible for designing, developing, and delivering production-grade AI solutions. The role combines strong software engineering and solution architecture expertise with hands-on experience in Generative AI, LLMs, RAG, Agentic AI, Model Context Protocol (MCP), AI-enabled SDLC, and Microsoft Azure.

The Technical Lead will translate business requirements into scalable AI solutions, provide technical direction to engineering teams, establish reusable patterns and guardrails, and ensure solutions meet enterprise requirements for security, reliability, performance, observability, cost, and Responsible AI.

Key Responsibilities & Technical Skills:

• Design and deliver enterprise AI solutions using LLMs, RAG, Agentic AI, enterprise knowledge retrieval, and intelligent automation
• Strong hands-on experience with Azure OpenAI, Microsoft Foundry/Azure AI services, and frameworks such as LangChain/LangGraph, Semantic Kernel, LlamaIndex, or comparable technologies
• Design prompt and context engineering, structured outputs, tool/function calling, agent orchestration, memory, and human-in-the-loop workflows
• Design and implement MCP servers/clients to securely connect AI agents with enterprise applications, APIs, data, and tools
• 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
• Design secure, scalable, resilient, observable, and cost-effective cloud architectures using appropriate Azure patterns
• 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
• Leverage 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, RBAC, 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/commercial technologies through prototypes and technical assessments
• Support client discussions, technical workshops, solutioning, demonstrations, and pre-sales activities as required

Work Location: This is a remote role open to candidates based in LATAM and supporting US-based clients.


Must Have Skills:

• 8+ years of experience in software engineering, solution architecture, or technical leadership
• Strong hands-on experience with Microsoft Azure and enterprise application architecture
• Demonstrated experience designing and developing Generative AI/LLM solutions, including RAG and agentic AI
• Experience taking AI solutions from prototype/PoC 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 SDLC
• Strong technical leadership, architecture, problem-solving, mentoring, and client communication skills
• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related discipline, or equivalent professional experience

Preferred Skills:

• Microsoft Azure Architecture or AI certifications
• Experience with enterprise RAG, knowledge architectures, and autonomous/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

Professional Skills:

• Solid written, verbal, and presentation communication skills
• Strong team and individual player
• Maintains composure during all types of situations and is collaborative by nature
• High standards of professionalism, consistently producing high quality results
• Self-sufficient, independent requiring very little supervision or intervention
• Demonstrate flexibility and openness to bring creative solutions to address issues

Bridgenext is an Equal Opportunity Employer



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