Agentic AI Technology Lead

We are seeking a highly experienced Agentic AI Technology Lead to design, architect, and deliver next-generation AI-driven business applications. This role requires a hands-on technical leader who can translate complex business needs into scalable AI solutions using modern LLM ecosystems such as ChatGPT (OpenAI), Gemini, and other enterprise AI platforms.

The ideal candidate will bring deep expertise in AI application design, prompt engineering, and full-stack AI solution development, combined with strong leadership experience managing globally distributed development teams in fast-paced, deadline-driven environments.

Key Responsibilities

AI Solution Architecture & Development Design, develop, and deploy agentic AI applications leveraging platforms such as OpenAI (ChatGPT), Google Gemini, and related LLM ecosystems Architect end-to-end AI-driven business workflows, including orchestration of multi-agent systems and tool integrations Lead the development of AI-enabled solutions using C++, TypeScript, and API-based architectures Apply advanced prompt engineering techniques to optimize AI outputs, accuracy, and contextual performance Design intuitive user interfaces and application experiences for AI-powered business tools Technical Leadership & Delivery Act as the technical lead for AI initiatives, making decisions on architecture, tooling, and implementation strategies Manage and coordinate offshore development teams, including non-native English-speaking engineers, ensuring clarity, efficiency, and delivery quality Drive execution within tight timelines and aggressive delivery schedules Provide hands-on support as needed in coding, debugging, and system integration Business Engagement & Process Analysis Collaborate directly with business stakeholders and subject matter experts (SMEs) to: Analyze existing business processes Identify automation and AI transformation opportunities Translate business requirements into technical specifications Operate effectively in a contractor/consultant capacity, adapting to varying client environments and expectations Security, Compliance & Data Governance Ensure strict adherence to security protocols and enterprise standards Design and implement solutions that securely handle and process PII (Personally Identifiable Information) Apply best practices for data privacy, access control, and risk mitigation in AI systems Maintain compliance with internal and regulatory requirements for AI usage and data handling Requirements Bachelor’s degree in Computer Science, Information Technology, or related field.

Technical Expertise Proven experience building AI applications using: OpenAI (ChatGPT), Gemini, or equivalent LLM platforms Strong programming skills in: C++ TypeScript Python Demonstrated expertise in: Prompt Engineering API integrations and microservices architecture AI/LLM orchestration and agent-based systems AI & Application Development Experience designing & developing AI business applications and intelligent automation use cases Strong understanding of: Conversational AI design Context management and memory handling in AI systems Experience in application UI/UX design for AI-driven interfaces is strongly preferred Experience managing offshore/global development teams Ability to communicate effectively across language and cultural barriers Proven track record of delivering high-quality solutions under tight deadlines Leadership & Delivery Experience managing offshore/global development teams Ability to communicate effectively across language and cultural barriers Proven track record of delivering high-quality solutions under tight deadlines Business & Consulting Skills Strong capability in business process analysis and solutioning Experience working directly with business stakeholders and SMEs Comfortable operating in contract-based or consulting roles Security & Compliance Deep understanding of: Secure application design PII data handling best practices Enterprise security protocols Experience working within regulated environments is a plus Preferred Qualifications Experience with agent frameworks (e.

g., Copilot, Semantic Kernel, custom orchestration frameworks) Familiarity with multi-agent architectures and RAG (Retrieval-Augmented Generation) systems Exposure to cloud platforms (Azure, GCP, AWS) supporting AI workloads Experience in enterprise automation ecosystems (RPA + AI integration)