AI Solutions Engineer

About the Role

Agentic Workflow Engineer

agents capable of executing these tasks end-to-end

Key Responsibilities

• Build & Deploy Agentic Workflows

  : Develop autonomous agents to handle operational tasks using LLMs, APIs, and automation frameworks.

• Leverage Existing Tools & Libraries

  : Identify, integrate, and optimize

  open-source libraries, agent frameworks, and online code repositories

  .

• Multi-Agent Orchestration

  : Design systems using

  MCP, ACP, or similar protocols

  for agent collaboration and tool usage.

• Systems Integration

  : Connect agents with internal systems, APIs, and third-party platforms for data flow and task execution.

• Optimization & Scalability

  : Improve agent performance, token usage, and deployment reliability.

• Collaborate with Business Teams

  : Translate manual workflows into automated solutions.

• Documentation

  : Maintain clear technical documentation for workflows and best practices.

Essential Skills & Knowledge

Must-Have:

• Programming

  : Expert in

  Python

  (async, multiprocessing); familiarity with

  JavaScript/Node.js

  for browser automation.

• Agent Frameworks

  : LangChain, AutoGen, CrewAI, or equivalent.

• Automation Tools

  : Selenium / Playwright for web automation.

• LLMs

  : Hands-on with OpenAI, Anthropic, or open-source models (prompt engineering & tool calling).

• Vector Databases

  : Pinecone, Weaviate, Chroma, or pgVector; strong understanding of embeddings & semantic search.

• Databases

  :

  PostgreSQL

  (schema design, query optimization).

• APIs & Integrations

  : RESTful APIs, GraphQL, OAuth, webhooks.

• Cloud & Deployment

  : Docker, Kubernetes, and AWS/GCP/Azure.

• Agent Orchestration

  : Knowledge of

  MCP (Model Context Protocol) and ACP (Agent Communication Protocol)

  .

Good-to-Have:

• Knowledge Graphs & reasoning systems.
• Experience with

  RPA bots

  or similar enterprise workflow automation.
• CI/CD pipelines for rapid deployment.
• Redis or similar for caching agent states.

Preferred Background

• 3–6 years in automation, RPA, or AI-driven workflow development.
• Prior experience building agent-based systems or LLM-powered automation tools.
• Exposure to

  multi-agent collaboration systems and enterprise integrations (CRM, ERP)

  .

What We Offer

• Opportunity to build cutting-edge agentic systems impacting real-world operations.
• Work in a fast-paced, innovation-driven environment with high autonomy.
• Competitive compensation and growth opportunities.