Project Manager

Responsibilities

GenAI Application Development

• Develop LLM-powered applications using Python-based frameworks.


• Implement RAG pipelines and vector database integrations.


• Build prompt orchestration workflows and response optimization logic.

Agentic Workflow Implementation

• Develop AI agents with tool integration capabilities.


• Implement reasoning loops, memory modules, and execution controls.


• Integrate AI agents into backend systems and APIs.

Deployment & Optimization

• Build REST APIs and microservices for AI applications.


• Optimize inference performance, latency, and cost.


• Support CI/CD pipelines and cloud deployments.

Testing & Quality

• Implement evaluation metrics for hallucination control and accuracy.


• Debug and resolve performance bottlenecks.


• Document code, workflows, and solution design.

Experience and Competency Requirements

• 4–8 years of software development experience.


• 2+ years working with AI/ML or GenAI applications.


• Strong proficiency in Python.


• Experience with LLM APIs, embeddings, and vector databases.


• Exposure to cloud-based deployments and containerization.


• Strong analytical and debugging capabilities.


• Should have decent to good experience in data handling and analytics with python

Skills

GenAI & LLM Frameworks (Mandatory)

• OpenAI APIs / Azure OpenAI


• LangChain / LangGraph / LlamaIndex


• Transformers (Hugging Face)


• Prompt engineering and evaluation frameworks

Agentic Systems & Orchestration

• Multi-agent design patterns (MCP, A2A, ReAct etc)


• Tool integrations and API orchestration


• Memory frameworks and contextual reasoning


• Guardrails, observability, and monitoring

Data & Infrastructure

• Vector databases (Pinecone, FAISS, Weaviate or equivalent)


• Python, FastAPI, REST services


• Docker, Kubernetes


• Cloud platforms (AWS, Azure, GCP)

Data Handling & Analytics Skills

• Data preprocessing and ETL for structured and unstructured data


• Data manipulation using Pandas, NumPy, and SQL


• Exploratory data analysis (EDA) and statistical analysis


• Data visualization (Matplotlib, Seaborn, Plotly, Tableau, Power BI)

Responsibilities

GenAI Application Development

• Develop LLM-powered applications using Python-based frameworks.


• Implement RAG pipelines and vector database integrations.


• Build prompt orchestration workflows and response optimization logic.

Agentic Workflow Implementation

• Develop AI agents with tool integration capabilities.


• Implement reasoning loops, memory modules, and execution controls.


• Integrate AI agents into backend systems and APIs.

Deployment & Optimization

• Build REST APIs and microservices for AI applications.


• Optimize inference performance, latency, and cost.


• Support CI/CD pipelines and cloud deployments.

Testing & Quality

• Implement evaluation metrics for hallucination control and accuracy.


• Debug and resolve performance bottlenecks.


• Document code, workflows, and solution design.

Experience and Competency Requirements

• 4–8 years of software development experience.


• 2+ years working with AI/ML or GenAI applications.


• Strong proficiency in Python.


• Experience with LLM APIs, embeddings, and vector databases.


• Exposure to cloud-based deployments and containerization.


• Strong analytical and debugging capabilities.


• Should have decent to good experience in data handling and analytics with python

Skills

GenAI & LLM Frameworks (Mandatory)

• OpenAI APIs / Azure OpenAI


• LangChain / LangGraph / LlamaIndex


• Transformers (Hugging Face)


• Prompt engineering and evaluation frameworks

Agentic Systems & Orchestration

• Multi-agent design patterns (MCP, A2A, ReAct etc)


• Tool integrations and API orchestration


• Memory frameworks and contextual reasoning


• Guardrails, observability, and monitoring

Data & Infrastructure

• Vector databases (Pinecone, FAISS, Weaviate or equivalent)


• Python, FastAPI, REST services


• Docker, Kubernetes


• Cloud platforms (AWS, Azure, GCP)

Data Handling & Analytics Skills

• Data preprocessing and ETL for structured and unstructured data


• Data manipulation using Pandas, NumPy, and SQL


• Exploratory data analysis (EDA) and statistical analysis


• Data visualization (Matplotlib, Seaborn, Plotly, Tableau, Power BI)

Minimum Qualification

Bachelor’s degree required

M.Tech/ MS in Computer Science, AI, or related field preferred; Required Experience: 4-6 years