Experience:
5 to 10+ years
Employment type:
Full time / Contract /Freelance
Location:
Bengaluru, Karnataka
About Company:
NexGen Architects is a London-based firm with a global reach, specializing in MuleSoft for seamless integration projects that support our clients' businesses in operating more effectively. Our hands-on experience is demonstrated through the success of integration solutions tailored for each client.
We offer a full range of services to our clients, focusing on creating strong Integration Architecture to ensure systems work together well, designing Solutions Architecture that addresses each business's unique challenges, and managing Enterprise Architecture that aligns technology strategies with business needs. Our approach includes the availability of "Hands-On Architects" and the flexibility of "On-Demand Architect hiring" in MuleSoft, providing the right expertise when it's needed.
Website:
https://www.nexgenarchitects.com/
Job Description
We are looking for an experienced
AI Agent Workflow Engineer
to design, build, and optimize intelligent agent workflows that combine LLMs, tools, APIs, and business logic. The role focuses on creating reliable, scalable agent systems that can plan, reason, and execute tasks across multiple integrations.
This is a fulltime role suited for engineers who have hands-on experience with AI agents beyond simple prompt usage.
Responsibilities
- Design and implement end-to-end AI agent workflows using LLMs.
- Build multi-step agent logic including planning, tool execution, memory, and retries.
- Integrate agents with external APIs, databases, and internal services.
- Implement routing logic, guardrails, and fallback strategies for reliability.
- Optimize prompts, context handling, and token usage for performance and cost.
- Debug agent behavior and improve accuracy, determinism, and observability.
- Collaborate with product and engineering teams to translate use cases into agent workflows.
- Document agent designs, workflows, and operational guidelines.
Requirements
- Strong experience building
AI agents or agent-based systems
in production.
- Hands-on experience with
LLMs
(OpenAI, Gemini, Anthropic, or similar).
- Experience with agent frameworks such as
LangChain, LangGraph, CrewAI, AutoGen
, or custom agent systems.
Nice to Have
- Experience with RAG systems and vector databases.
- Experience building multi-agent systems or hierarchical agents.
- Familiarity with evaluation, monitoring, and tracing of AI agents.
- Knowledge of async workflows and distributed systems.
