Gen AI Engineer / Applied AI Engineer
Indexed description
You will work on building intelligent systems using RAG (Retrieval Augmented Generation), AI agents, and data pipelines — not just simple API integrations. The role requires both software engineering and practical AI problem-solving skills.
This is an applied engineering role where you will design and implement production-grade Gen AI applications rather than research-only experimentation.
Tech Environment
- Google Cloud Platform (GCP)
- Vertex AI & Gemini Models
- Python
- RAG Architectures
- Cloud Run deployments
- Data stores (SQL / NoSQL / Vector DBs)
- Gen AI Agents & workflow automation
- Design and implement Generative AI applications using Vertex AI and Gemini
- Build RAG pipelines integrating structured and unstructured data
- Develop AI agents for workflow automation and task orchestration
- Create intelligent assistants and automated decision systems
- Design data ingestion pipelines for AI consumption
- Work with embeddings, vector search, and knowledge retrieval
- Integrate databases, document stores, and business data sources into AI workflows
- Improve response quality using prompt design, retrieval logic, and evaluation
- Automate product flows and operational processes using AI agents
- Build systems that assist internal teams in data analysis and decision-making
- Develop solutions to simplify business workflows and reduce manual operations
- Deploy AI services on GCP (Cloud Run / APIs)
- Integrate AI features with backend services and applications
- Optimize cost, latency, and reliability of Gen AI workloads
- Use Gen AI techniques to solve complex algorithmic and data processing problems
- Evaluate model outputs and continuously improve performance
- Create reusable AI frameworks and utilities
- Strong Python programming (minimum 2 years)
- Hands-on experience with Generative AI tools (minimum 2 years)
- Good understanding of data models and data processing
- Practical implementation of RAG architectures
- Experience using Vertex AI or similar cloud AI platforms
- Working knowledge of Gemini / LLM APIs
- Understanding of AI agents and orchestration concepts
- Experience with GCP services (preferred)
- Deploying services using Cloud Run or containerized APIs
- Working with databases and data stores (SQL/NoSQL)
- Handling large datasets and document collections
- Prompt engineering and evaluation techniques
- Embeddings and vector search concepts
- Handling hallucinations and improving answer accuracy
- API integration and microservices communication
- Ability to build complete GenAI solutions, not just call APIs
- Strong debugging and problem-solving mindset
- Interest in applying AI to real business problems
- Ownership mindset and experimentation attitude
- Ability to learn and adapt quickly in a fast-evolving AI ecosystem
- Experience with vector databases (Pinecone, Weaviate, FAISS, etc.)
- Experience with LangChain, LlamaIndex, or agent frameworks
- Knowledge of NLP fundamentals
- Experience building chatbots or AI assistants
- Exposure to data pipelines or ETL systems
- Experience optimizing LLM cost and latency
Benefits
Why Join Us
- Opportunity to work on real production Gen AI systems
- Build AI automation impacting business workflows
- Hands-on experience with Vertex AI & Gemini ecosystem
- Work on challenging data and algorithmic problems
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