Ml Agentic Ai Engineering Lead Programmer Analyst Bilvantis Technologies Hyderabad

vibehackers; Hyderabad; In loco; INR 1.800.000 - 3.000.000; Tempo pieno

Descrizione del lavoro

Bilvantis Technologies in Hyderabad seeks a Lead Programmer Analyst (ML / Agentic AI) to own end-to-end production ML solutions, from data prep and model evaluation to deployment and monitoring. You will guide engineers and ensure high-quality delivery of autonomous agentic workflows.

Responsibilities include shaping ML/AI outcomes, building RAG apps, validating models, and maintaining scalable services with strong collaboration across teams.

Competenze

• 5+ years of professional software/ML engineering with hands-on production ML delivery.
• Strong Python and SQL skills with data prep and feature engineering experience.
• Experience building LLM/agentic AI apps, RAG workflows and vector stores.

Mansioni

• Translate business problems into measurable ML/AI outcomes with clear milestones.
• Prepare data, engineer features and train models for various tasks.
• Build RAG apps and stateful agents integrating APIs and model outputs.
• Implement validation, monitoring, retraining and experiment tracking.
• Ensure deployment quality via APIs, containers and cloud platforms, with cost controls.
• Mentor junior engineers through reviews and hands-on guidance.

Conoscenze

Python

SQL

pandas

NumPy

scikit-learn

XGBoost

LLM APIs

Embeddings

Vector search

RAG

LangChain

FastAPI

Git

Cloud platforms

Strumenti

LLamaIndex

pgvector

Qdrant

Docker

Kubernetes

TensorFlow

PyTorch

MLflow

Descrizione del lavoro

Ml Agentic Ai Engineering Lead Programmer Analyst Bilvantis Technologies Hyderabad

Builds agentic LLM apps and RAG pipelines (LangChain/LlamaIndex) with vector stores and model-serving — hands-on agentic AI work.

About the Role

Lead ML/Agentic AI Engineer responsible for end-to-end delivery of production ML and LLM/agentic AI solutions, from data preparation and model evaluation through deployment and monitoring, while mentoring junior engineers and ensuring engineering quality.

Job Description

Role

Lead Programmer Analyst (ML / Agentic AI) responsible for building and delivering production ML solutions that integrate predictive models with LLM applications and autonomous agentic workflows. Own implementation from data preparation and model evaluation through deployment, monitoring and retraining, and provide technical leadership and mentorship to junior engineers.

Key Responsibilities

• Translate business problems into measurable ML/AI outcomes, define baselines and success metrics, and produce delivery plans.
• Prepare datasets, engineer features, and train models for classification, regression, forecasting or anomaly detection.
• Build RAG applications and stateful agents that retrieve knowledge, call business APIs, and incorporate predictive model outputs into workflows.
• Implement model validation, experiment tracking, reproducible pipelines, prediction services, monitoring and retraining processes.
• Implement permissions, approvals, failure recovery and cost controls for agent workflows and model services.
• Serve models through web services and maintain deployment/operational quality (APIs, containers, cloud platforms).
• Review designs and code, guide and mentor junior engineers through pairing, code reviews and practical assignments, and take ownership of delivery quality.

Requirements

• 5+ years of professional experience in software engineering, data science or ML engineering with hands-on delivery of production ML solutions and practical LLM/agentic AI applications.
• Strong Python and SQL skills.
• Experience with data preparation and ML libraries such as pandas, NumPy, scikit-learn and XGBoost (or equivalent).
• Solid understanding of statistics, feature engineering, class imbalance, cross-validation, data leakage, overfitting and model explainability.
• Experience with LLM APIs, prompt/context design, structured outputs, embeddings, vector search, RAG and tool/function calling.
• Experience with LangChain (or equivalent) for LLM integration and stateful agents including approvals, retries and execution limits.
• Experience serving models via FastAPI or Flask; working knowledge of Git, automated tests, containers and a cloud platform.
• Ability to explain model trade-offs to stakeholders and diagnose data, model and application failures.

Preferred / Nice-to-have

• Exposure to CrewAI or LangGraph for agent orchestration and multi-agent workflows.
• Deep learning experience with PyTorch or TensorFlow/Keras and Hugging Face Transformers.
• MLflow for experiments and model tracking; LlamaIndex for RAG; vector stores such as pgvector or Qdrant.
• Time-series modelling, open-model serving, enterprise integrations and sensitive-data handling.

Python SQL pandas NumPy scikit-learn XGBoost LLM APIs embeddings vector search RAG LangChain FastAPI Flask Git containers cloud platform CrewAI LangGraph PyTorch TensorFlow Keras Hugging Face Transformers MLflow LlamaIndex pgvector Qdrant

Skills