Agentic AI Developer
LangGraph, CrewAI, AutoGen, multi-agent systems
Indicative CTC
17.8 LPA
Indian market, not an offer
Interview rounds
5
typical loop
Track length
12 months
program structure
What the work involves
Day-to-day work, not the job description version.
- Design agent loops: what decides, what acts, what stops, and how it recovers
- Add tools and permissions without opening a security hole
- Build multi-agent systems that fail in comprehensible ways
- Evaluate agent behaviour, which is harder than evaluating a single model call
What employers test
The skills that decide whether you clear the loop.
- Agent loop design and state management
- At least one framework deeply (LangGraph or CrewAI)
- Tool design and MCP
- Multi-agent orchestration and its failure modes
- Agent evaluation and tracing
Salary bands
Indicative Indian market ranges for this role, not Avolute-AI graduate offers. Bands, not guarantees.
14-18 LPA
Common for backend engineers moving into agent work
18-25 LPA
The band most candidates in India land in
25+ LPA
Fewer openings, higher ceiling, and more competition
How the program covers it
Where this role sits across the 12 months.
Months 1-3
Software engineering and LLM fundamentals first
Months 4-6
Agent loops, planning, memory, and the first LangGraph project
Months 7-9
MCP, multi-agent systems, evaluation and tracing
Months 10-12
A production agent with real tools and real permissions
The interview loop
What each round is actually checking.
- 01
Screening
Backend or systems background
- 02
DSA
Standard data structures
- 03
Agent design
Loop design, state, failure recovery
- 04
System design
A multi-agent system with tools
- 05
Project deep-dive
Why your agent terminates and stays safe
We run mock interviews on this structure from month seven, including a full-length system design round timed the same way a real one is.
Questions
Are agent frameworks a fad?
The frameworks change often. The underlying ideas, which are state management, tool boundaries, termination conditions and recovery, do not. We teach the ideas and use one framework concretely, rather than chasing every release.
How do you test an agent?
Differently from normal code. You evaluate trajectories rather than single outputs, check that it terminates, and test the failure paths explicitly. This is covered in the evaluation module of the flagship track.