Agentic AI/ML on w2

Role Summary

This role is focused on building agentic AI systems and establishing a core AI capability within the organization. The engineer will design, develop, and deploy advanced AI agents and create foundational frameworks for future AI-driven solutions.

Key Responsibilities

Core Development & Architecture

Analyze, design, develop, test, and implement complex applications Build enterprise-level applications and custom integrations Design, code, debug, and document software solutions Evaluate system interdependencies and impacts of changes AI & Advanced Systems

Develop and deploy agentic AI systems Build frameworks for generative AI use cases Research, test, and optimize AI models and agent frameworks Monitor and improve AI behavior in production environments Technical Leadership (20%)

Lead integration of applications across business systems Design scalable structures and solutions for enterprise software Consulting & Collaboration (15%)

Act as internal consultant and mentor Work with stakeholders to define business and technical requirements Ensure alignment with IT strategy and architecture standards Strategic Design & Innovation (15%)

Recommend long-term IT and architecture improvements Evaluate build vs. buy decisions Contribute to data and component architecture design System Development & Problem Solving (15%)

Solve complex business and technical problems Develop new approaches, techniques, and data sources Standards & Lifecycle Management (15%)

Define development standards and best practices Participate in full SDLC (design → deployment → support) Ensure timely and budget-conscious delivery Leadership & Mentorship (15%)

Guide junior developers and analysts Lead or coordinate complex projects Resolve cross-team technical issues Testing & Documentation (5%)

Perform testing, debugging, and validation Maintain technical documentation Required Skills & Qualifications

Education

Bachelor’s degree in Computer Science, IT, or related field OR 4 years relevant experience OR Associate’s degree + 2 years relevant experience Experience

8+ years in application development, systems testing, or related fields 3–6 years in AI/ML or related domains Technical Skills

Core Technologies

Python (advanced proficiency) JavaScript / TypeScript API design AI / ML & Agentic Systems

Generative AI development (end-to-end) Agentic AI concepts (reasoning, planning, tool use) Prompt engineering, RAG, and AI system design Experience with AI models (e.g., OpenAI, Claude) Frameworks & Tools

LangChain, LangGraph, and similar frameworks AI agent development tools and ecosystems Infrastructure & DevOps

AWS (preferred) or other cloud platforms CI/CD pipelines Docker & Kubernetes GitHub and modern development workflows Systems Knowledge

Multi-platform environments (mainframe, midrange, PC/LAN) Software architecture and system integration Performance monitoring and optimization Nice-to-Have Skills

FastAPI or Flask SQL and database experience AutoGen, MCP, embeddings, knowledge stores Reinforcement learning and planning algorithms Multi-agent systems Multi-cloud experience (AWS, Azure, Google Cloud Platform) Model fine-tuning and advanced prompt engineering Soft Skills

Strong analytical and problem-solving abilities Effective verbal and written communication Ability to work under pressure in fast-paced environments Team collaboration and leadership skills Attention to detail Strong interpersonal and relationship-building skills Work Environment

Fast-paced, project-oriented environment Multi-platform technical ecosystem May require occasional 24/7 responsiveness Strong focus on innovation, collaboration, and customer needs Day-to-Day Activities

Hands-on Python development for AI systems Designing and implementing AI architectures Integrating AI agents with backend services Deploying solutions via CI/CD pipelines Researching and testing new AI models/frameworks Collaborating with data scientists and stakeholders Monitoring and improving production AI systems Not a Fit If

Experience is limited to traditional ML (e.g., regression/classification) Lack of exposure to Generative AI or agentic systems Team & Culture

Innovative, collaborative, and fast-paced Focused on building next-generation enterprise AI solutions Emphasis on creativity, continuous learning, and impact Opportunity to shape long-term AI strategy

Requires strong hands-on Python skills and a deep understanding of end-to-end RAG pipeline design. Must explain the full RAG implementation and Python programming proficiency.