We are looking forward to hire AI Professionals in the following areas :

Key Responsibilities

- Agent Architecture & Development
- Design and implement agentic AI architectures, including:

- ReAct (Reason + Act)
- Plan-and-Execute
- Tool-using agents
- Multi-agent systems and coordinators
- Build LLM-powered applications using modern foundation models
- Translate business use cases into reliable, scalable agent workflows with clear handoffs and fallbacks
- LLM & RAG Engineering
- Develop and optimize prompt engineering strategies for reasoning, task execution, and tool use.
- Implement Retrieval-Augmented Generation (RAG) pipelines using structured and unstructured data.
- Design and manage agent memory systems, including:
- Short-term (conversation/state)
- Long-term (vector-based memory)

- Work with vector databases
- Tooling, APIs & Integration
- Build and integrate internal and external tools (APIs, microservices, enterprise systems).
- Enable agents to safely interact with:

- Databases

- Business applications

- Automation platforms

- Cloud services
- Ensure robust error handling, retries, and fallback logic .
- Production Readiness & Operations
- Deploy agentic systems into production environments.
- Implement monitoring, logging, and evaluation frameworks for:

- Accuracy and task success

- Latency and cost efficiency

- Safety and policy compliance
- Design and enforce guardrails to prevent hallucinations, unsafe actions, or data leakage.
- Continuously optimize system performance and cost
- Collaboration & Delivery
- Partner closely with business stakeholders, application developers, data teams, and business stakeholders.
- Act as a technical product owner for agentic solutions: collect user and business requirements, clarify problem statements, and translate them into system designs and implementation plans




- Identify high-impact AI opportunities and rapidly prototype, validate, and scale solutions.
- Contribute to internal best practices, architecture standards, and AI governance.
- Lead agentic tooling decisions: evaluate frameworks, model providers, orchestration patterns, and integration approaches; make pragmatic build/buy choices aligned to security, reliability, and cost constraints.
- Act as a technical product partner: collect user requirements, define success metrics and acceptance criteria, translate needs into solution designs and implementation plans, and drive delivery from prototype to production.

- Required Qualifications
- Bachelor s degree in Computer Science, Computer Engineering, Information Technology, or equivalent experience.
- 3+ years of professional software development experience.
- Strong proficiency in Python (required).
- Hands-on experience working with LLM APIs, and MCP

- Solid understanding of

- Prompt engineering

- Embeddings and semantic search
- Retrieval-Augmented Generation (RAG)
- API and backend system design
- Experience integrating AI systems into production applications.
- Familiarity with cloud platforms (Azure, AWS, or GCP).
- Strong problem-solving skills and ability to manage multiple priorities in fast-paced environments.

Excellent written and verbal communication skills in English Our Hyperlearning workplace is grounded upon four principles

- Flexible work arrangements, Free spirit, and emotional positivity
- Agile self-determination, trust, transparency, and open collaboration
- All Support needed for the realization of business goals,
- Stable employment with a outstanding atmosphere and ethical corporate culture

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Agentic AI Engineer (Pune)
🏢 Yash Technologies
📍 Pune