Job Description:
Senior AI Engineer — GenAI Solutions
Viamagus Technologies Pvt. Ltd.
Hyderabad
4–7 years
Today
$33.7K–53.0K/yr
Full-time
Onsite
Skills Required
- LLM
- RAG
- Gen AI
- LangChain
- Embeddings
- Vector Database
- retrieval
- LLM observability
- multimodal applications
- LangGraph
- FastAPI
- Python
- Pinecone
- Weaviate
- pgvector
Description
Senior AI Engineer role focused on building production‑grade GenAI solutions and client‑facing solutioning. This is a founding role for a new AI Consulting & Engineering practice serving enterprise and Fortune 500 clients.
Company
Viamagus Technologies Pvt. Ltd.
Role
Senior AI Engineer — GenAI Solutions
Location
Hyderabad, India
Experience
- 4–7 years of software engineering experience
- At least one real production LLM‑powered feature shipped
- Hands‑on experience with production GenAI, RAG, and agentic systems
- Fluent written and spoken English
Responsibilities
- Design and build production GenAI applications including LLM copilots, RAG pipelines, agentic workflows, and AI‑native UX
- Engineer retrieval end to end, including chunking, embeddings, vector stores, retrieval, re‑ranking, and hybrid search
- Build agents and multi‑step workflows with LangGraph and LangChain
- Integrate MCP servers and agent SDKs for tool access
- Augment enterprise platforms with predictive insight, intelligent automation, and conversational UX
- Deploy solutions on AWS Bedrock, Azure AI Foundry, or GCP Vertex AI with CI/CD, observability, and guardrails
- Build evaluation harnesses and wire up LLM observability
- Handle responsible‑AI basics including PII handling, guardrails, and audit trails
- Run client discovery workshops and translate business problems into scoped, ROI‑backed AI use cases
- Demo working software to technical and business stakeholders and defend design decisions and tradeoffs
- Contribute to reusable accelerators
- Mentor junior engineers as the practice grows
Additional Responsibilities
- Work in a roughly 70% hands‑on engineering and 30% client‑facing solutioning split
- Take AI use cases from discovery workshop to deployed, monitored production system
- Build AI solutions for enterprise and Fortune 500 clients, not disconnected proofs of concept
- Help shape the architecture, standards, and culture of a new AI practice
- Work across a modern 2026 AI stack
- Ensure every engagement is tied to a business KPI
Nice To Have
- Experience adding AI to enterprise platforms such as Clarity PPM, Medallia, ServiceNow, or Salesforce Einstein
- Deeper MLOps experience with MLflow, Weights & Biases, model monitoring, or serverless GPU
- Data and RAG infrastructure experience with ETL/ELT, CDC, orchestration, streaming, knowledge graphs, Databricks, or Snowflake
- Fine‑tuning and multimodal experience including LoRA, distillation, vision, voice, or multimodal applications
- Industry domain depth in financial services, insurance, healthcare, or retail
- AI governance awareness including NIST AI RMF and EU AI Act
- Relevant cloud AI/ML certifications
More Skills
LLM-powered features, Prompt design, Structured outputs, Tool/function calling, Streaming, Chunking, Qdrant, Re‑ranking, Hybrid search, LlamaIndex, MCP, Agent SDKs, TypeScript, React, Next.js, AWS Bedrock, Azure AI Foundry, GCP Vertex AI, Docker, CI/CD, Evaluation harnesses, LangSmith, Langfuse, Arize, PII handling, Guardrails, Azure AI Foundry, GCP Vertex AI