Technical Lead

Job Title: Technical Lead

Job Description

The Agentic AI Architect / Technical Lead will serve as the primary technical authority for designing and delivering large-scale Agentic AI solutions. This role acts as a critical bridge between product strategy, customer requirements, and engineering execution, requiring a strong blend of AI expertise, system architecture, and leadership skills.

The Architect will be responsible for leading architecture definition, driving complex proof-of-concept initiatives, enabling multi-agent system design, and managing cross-functional engineering teams. The role demands deep experience in LLM ecosystems, cloud-native platforms, and scalable system design to deliver robust, production-grade AI platforms with measurable business outcomes.

Key Responsibilities

• Solution Architecture: Lead the design and development of scalable, secure, and high-performance architectures for Agentic AI platforms using Python and modern frameworks
• Technical Standards & Deliverables: Define architecture patterns, engineering standards, and best practices for development, deployment, and system scalability
• Collaboration: Work closely with product managers, engineering teams, DevOps, and QA to align technical solutions with business requirements and ensure seamless system integration
• Stakeholder Interaction: Lead and execute technical POCs for Agentic AI solutions, working with customer stakeholders to define success criteria, build tailored agent configurations, and demonstrate business impact
• Agent Orchestration: Architect and implement multi-agent workflows using frameworks such as LangGraph, AutoGen, or CrewAI, ensuring alignment with real-world use cases
• Platform Development: Design and build resilient, scalable, multi-tenant AI platforms that support continuous innovation and production deployment
• Evaluation & Benchmarking: Own the design and implementation of LLM and agent evaluation frameworks, including metrics for accuracy, hallucination, safety, and performance
• Performance Optimization: Optimize system architecture and infrastructure for scalability, latency, and cost-efficiency across AI workloads
• Best Practices: Establish and enforce standards across MLOps, AIOps, CI/CD, model versioning, experimentation tracking, and system observability
• Leadership & Mentorship: Provide technical leadership, guide architectural decisions, and mentor engineering teams to ensure high-quality delivery
• Innovation & Research: Stay updated with advancements in AI, LLMs, and agentic frameworks, continuously improving system capabilities
• Documentation: Create and maintain comprehensive architectural and technical documentation

Required Skills & Qualifications:

• 12+ years of experience in software engineering with strong expertise in Python and backend system development

• Extensive experience in designing scalable, secure, multi-tenant AI/ML platforms

• Deep expertise in LLMs (OpenAI, Gemini, Anthropic, Llama) and agentic AI systems

• Hands-on experience with agent frameworks such as AutoGen, CrewAI, LangGraph, and LangChain ecosystem (LangChain, LangSmith, LangFlow)

• Strong experience building RAG-based systems and working with vector databases

• Proficiency in Python ecosystem including PyTorch, Scikit-learn, LlamaIndex, and evaluation tools like DeepEval

• Deep understanding of LLM concepts (prompt engineering, fine-tuning, function/tool calling, RAG)

• Strong experience in microservices architecture, REST APIs, and event-driven systems

• Expertise in relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Redis)

• Experience with cloud platforms (AWS, Azure, GCP) and cloud-native architectures

• Familiarity with Docker, Kubernetes, and modern DevOps practices

• Experience with CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions)

• Strong exposure to observability tools for logging, monitoring, and tracing AI systems

• Strong understanding of system design, scalability, and engineering best practices

• Proven ability to lead architectural discussions, mentor teams, and engage with stakeholders and clients

• Compensation, Benefits and Duration

• Minimum Compensation: USD 46,000

• Maximum Compensation: USD 162,000

• Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.

• Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.

• This position is not available for independent contractors

• No applications will be considered if received more than 120 days after the date of this post.

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