603 Senior Python Engineer Ai Coding Agent Evaluation Freelance jobs near me

Job Summary:

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.