Job Role: AI/ML Engineer (Agentic AI Focus)

Experience: 6 - 8 Years

Location: Hyderabad

Work Mode: 5 Days Onsite

Working Hours: 11 AM 9 PM

Notice Period: Immediate to 15 Days

Email your CV: [email protected]

JD-

1. Core Programming & Systems Skills

- Python (expert level) for ML, orchestration, and agent logic.
- Strong understanding of async programming, concurrency, and task scheduling.

2. Foundations of Agentic AI

- Design and implementation of autonomous AI agents capable of:
- Multi-step reasoning and planning.
- Goal decomposition and task orchestration.
- Agile decision-making under uncertainty.

- Experience with agent architectures
- ReAct.
- Plan-and-Execute.
- Reflexive agents.
- Hierarchical / multi-agent systems.
- Tool-augmented and function-calling agents.
- Understanding of stateful vs. stateless agents and memory management.

3. Large Language Models (LLMs)

- Hands-on experience with LLMs:
- OpenAI.
- Azure OpenAI.
- Anthropic.
- Open-source models.
- Prompt-engineering techniques for:
- Reasoning (Chain-of-Thought, Self-Reflection).
- Planning and critique loops.
- Instruction following and tool use.

- Experience with
- Few-shot and zero-shot prompting.
- Model selection trade-offs (latency, cost, context length).
- Knowledge of fine-tuning / adapters (LoRA) is a plus.

4. Agent Frameworks & Tooling

- Practical experience with agent frameworks, such as:
- LangGraph / LangChain (agents, tools, memory).
- Semantic Kernel.
- AutoGen, CrewAI, or similar.
- Ability to build custom agent orchestration layers beyond frameworks.
- Tool abstraction and execution safety:
- Timeouts.
- Retries.
- Sandboxing.

5. Memory, Context & Knowledge Augmentation

- Design of agent memory systems:
- Short-term (conversation/state memory).
- Long-term (episodic, semantic memory).
- Retrieval-Augmented Generation (RAG):
- Vector databases (FAISS, Pinecone, Azure AI Search, etc.).
- Embedding selection and chunking strategies.
- Techniques for context management and compression.




- Knowledge graph–augmented or hybrid memory is a plus.

6. Planning, Reasoning & Control

- Experience implementing:
- Task planners (step planning, re-planning).
- Constraint-based execution.
- Feedback and self-correction loops.

- Understanding of
- Tool reliability scoring.
- Guardrails and action validation.
- Failure detection and graceful recovery.

7. MLOps & AgentOps

- Deployment of agents into production environments.

- Observability for agents
- Tracing agent decisions and tool calls.
- Logging prompts, responses, and errors.
- Model and prompt versioning.
- CI/CD for agent systems.
- Experience with Docker, Kubernetes, serverless deployments (Azure/AWS).

8. Evaluation & Testing of Agentic Systems

- Designing evaluation frameworks for agents:
- Task success rate.
- Cost, latency, and reliability.
- Safety and hallucination detection.
- Offline test harnesses and simulation environments.
- A/B testing of prompts, tools, and agent strategies.

9. Security, Safety & Responsible AI

- Secure tool execution and privilege control.
- Prompt-injection and jailbreak risk mitigation.
- Data privacy and isolation in agent memory.

- Responsible AI practices
- Bias awareness.
- Explainability of agent decisions.
- Human-in-the-loop escalation patterns.

10. Data & Integration Skills

- Integration with:
- Enterprise systems (CRM, ERP, databases).
- Web services, internal APIs, and SaaS tools.

- Working knowledge of
- SQL / NoSQL databases.
- Event-driven systems and message queues is a plus.

11. Cloud & Platform Expertise

- Strong experience with at least one cloud platform:
- Azure (preferred for enterprise agentic AI).
- AWS.
- GCP.
- Managed AI services, identity & access, and secrets management.
- Cost optimization for LLM-driven systems.

12. Bonus / Advanced Skills (Nice to Have)

- Multi-agent collaboration and negotiation.
- Human-AI collaboration patterns (copilots, supervisors).
- Reinforcement learning for agent policy optimization.
- Experience building enterprise copilots or autonomous workflows.

📌 Artificial Intelligence Engineer (Hyderabad)
🏢 Neptron Technologies
📍 Hyderabad