Job Description :

About Ergobite :

At Ergobite, we partner with startups and enterprises to deliver high-quality product engineering and solution development. Our expert teams accelerate software innovation across diverse technology stacks, including AI, MEAN, MERN, Java, Flutter, Swift, and Python. We bring strong capabilities in cloud platforms such as AWS, Google Cloud, and Azure, ensuring scalable and secure deployments. For startups, we also leverage Digital Ocean to achieve significant cost optimization during both development and growth phases.

With a focus on speed, reliability, and future-ready architectures, Ergobite empowers businesses to transform ideas into production-grade solutions that drive measurable impact.

Role Overview :

We are seeking a mid-level Agentic AI / RAG Engineer with 3+ years of professional software engineering experience and hands-on exposure to AI/ML systems. You will design and implement retrieval-augmented generation (RAG) pipelines, agentic workflows, and enterprise-ready AI applications. This role offers the opportunity to work across diverse customer projects while contributing to the foundation of Ergobites agentic AI practice.

Key Responsibilities :

RAG Development :

- Build and optimize retrieval pipelines : smart chunking, hybrid retrieval (BM25 + dense), reranking, query rewriting.

- Work with vector databases (Qdrant, Weaviate, Pinecone, OpenSearch) for scalable search.

- Implement multi-hop retrieval and knowledge graph basics.

Agentic AI Workflows :

- Design LangChain/LangGraph-based agent workflows with planning, reasoning, tool usage, and memory.

- Build multi-agent orchestration pipelines for collaboration and autonomous execution.

- Integrate external APIs, MCP tools, and enterprise systems into agent workflows.

LLM Ops & Model Engineering :

- Apply prompt engineering and evaluation frameworks to improve reliability.

- Fine-tune or adapt models using LoRA/PEFT techniques.

- Implement guardrails and hallucination reduction strategies.

Backend & Infrastructure :

- Develop FastAPI/Django-based microservices with async execution and caching.

- Containerize workloads using Docker and deploy on AWS/Azure/GCP.

- Contribute to CI/CD pipelines and cloud-native deployments.

Data Engineering & Governance :

- Build document ingestion pipelines (PDF, DOCX, OCR, images).

- Ensure compliance with PII handling, audit trails, and responsible AI practices.

Core Skills :

- Programming : Python (strong), FastAPI/Django; familiarity with React/Node.js is a plus.

- AI/ML : LLM integration, embeddings, transformers, RAG frameworks (LangChain, LlamaIndex, Haystack).

- Vector Databases : Qdrant, Weaviate, Pinecone, OpenSearch/Elasticsearch.

- Cloud & DevOps : AWS/Azure/GCP basics, Docker, Kubernetes, CI/CD.

- MLOps/LLMOps : Model deployment, monitoring, evaluation frameworks.

- Security & Compliance : RBAC, audit readiness, responsible AI practices.

Preferred Qualifications :

- 3+ years of professional software engineering experience, with at least 1-2 years in AI/ML or Generative AI.

- Experience building production-ready AI systems (not just prototypes).

- Familiarity with multi-agent orchestration and enterprise-scale integrations.

- Exposure to retrieval strategies, vector databases, and RAG architectures.

- Strong problem-solving and communication skills for customer-facing delivery.

What We Offer :

- Opportunity to grow into practice leadership roles as Ergobite scales its agentic AI practice.

- Hands-on exposure to diverse customer projects across industries.

- Collaborative, growth-oriented environment with mentorship and career development.

- A chance to pioneer next-generation AI solutions with real-world impact.