Lead Ai engineer

Bellcom Technologies; Bhopal; On-site; INR 3,600,000 - 6,000,000; Full time

Job summary

Bellcom Technologies in Bhopal is seeking a hands-on Lead AI Engineer to anchor the technical delivery of a large-scale enterprise AI/ML programme in the financial tech domain. You will guide a team of data scientists, MLOps, RPA, and full-stack engineers, drive architecture decisions, code reviews, and client sign-offs.

The role requires 8+ years in software/AI with 3-4 years delivering end-to-end AI/ML projects, strong Python, and hands-on ML deployment experience.

Qualifications

• 8+ years of software/AI engineering experience with 3-4 years in end-to-end AI/ML project delivery.
• Strong Python skills and deep ML fundamentals across supervised, unsupervised, time-series, NLP.
• Proven track record of delivering production-grade ML systems, not just PoCs.
• Solid data engineering background: ETL, Spark, Data Lake/DW; MLOps tooling; CI/CD for ML.
• Excellent communication to present technical content to non-technical stakeholders.

Responsibilities

• Define and own end-to-end solution architecture including AI/ML platform, MLOps, data infra and integration layers.
• Lead multiple AI/ML workstreams: forecasting, anomaly detection, risk scoring, document AI, chatbot.
• Conduct code reviews, model validation, and API design reviews across workstreams.
• Lead architecture workshops and secure formal sign-offs from stakeholders.
• Manage cross-team dependencies between data engineering, MLOps, apps and integration workstreams.
• Enforce coding standards, SDLC docs, and test coverage thresholds.
• Mentor Senior Data Scientists, MLOps, Full-Stack, and Data Engineering teams.
• Manage technical risks including data quality, model accuracy, API stability, and security.
• Ensure proper versioning of source code, artifacts, and docs in SCM.
• Lead handover, code walkthroughs, and knowledge transfer at project close.

Skills

Python

ML fundamentals

Production-grade ML

Data engineering

Spark

Airflow

MLOps

CI/CD for ML

RPA (UiPath/Robot Framework)

Microservices

REST API design

Docker/Kubernetes

SDLC documentation

Enterprise delivery

Stakeholder communication

Education

B.Tech / M.Tech / M.S. in CS/AI/DS

Tools

MLflow

Kubeflow

UiPath

Robot Framework

Docker

Kubernetes

Spark

Airflow

Job description

Job Description
Lead AI Engineer
Number of Openings
Location
1
Bhopal, Madhya Pradesh (On-site, Full-Time)
Reports To
Project Manager / Delivery Head
8+ Years
Full-Time, On-site
Experience Required
Employment Type
Domain
AI/ML, Financial Technology

Role Overview
We are looking for a hands-on Lead AI Engineer to anchor the technical delivery of a large-scale enterprise
AI/ML programme in the financial domain. This role owns end-to-end technical quality from solution
architecture and data pipelines through to model deployment and FMS integration. The Lead bridges strategy
and execution: guiding a team of data scientists, MLOps, RPA, and full-stack engineers; conducting design and
code reviews; and representing the technical team in all formal milestone reviews and client sign-offs.

Key Responsibilities

• Define and own the end-to-end solution architecture: AI/ML platform, MLOps pipeline, data infrastructure (Data Lake/DW), RPA orchestration, and enterprise application integration layer.
• Lead the technical delivery of multiple concurrent AI/ML workstreams spanning forecasting, anomaly
  detection, risk scoring, document AI (OCR), classification, and conversational AI (chatbot).
• Conduct hands-on code reviews, model validation reviews, and API design reviews across all
  workstreams.
• Lead technical requirement workshops with enterprise stakeholders; prepare and present architecture
  and design documents for formal sign-offs.
• Resolve cross-team dependencies between data engineering, MLOps, application, and integration
  workstreams.
• Define and enforce coding standards, SDLC documentation quality, and test coverage thresholds across the team.
• Mentor and guide Senior Data Scientists, MLOps, Full-Stack, RPA, and Data Engineering team members.
• Manage technical risks: data quality gaps, model accuracy issues, API instability, and security compliance.
• Ensure all source code, model artefacts, and documentation are properly versioned and maintained in
  SCM throughout delivery.
• Lead final handover, code walkthrough, and knowledge transfer at project close.

Required Skills & Experience

• 8+ years of overall software/AI engineering experience; minimum 3-4 years in end-to-end AI/ML project
  delivery.
• Strong hands-on Python proficiency; deep understanding of ML fundamentals across supervised,
  unsupervised, time-series, anomaly detection, and NLP domains.
• Proven track record of delivering production-grade ML systems not just prototypes or PoCs.

• Solid data engineering background: ETL pipelines, Apache Spark, Airflow, Data Lake/DW architecture.
  MLOps tooling experience: MLflow, Kubeflow or equivalent; CI/CD for ML models.
  Familiarity with RPA platforms (UiPath / Robot Framework) and AI document processing pipelines.
  Microservices architecture, REST API design, Docker/Kubernetes.
  Experience with formal SDLC deliverables (SRS, HLD, LLD) and milestone-based delivery in large enterprise
  or government/PSU programmes.
• Strong communication skills ability to present technical content clearly to non-technical stakeholders.

Preferred / Good to Have

• Prior experience in financial domain AI/ML: transaction monitoring, forecasting, vendor/credit risk
  scoring.
• Experience with open-source LLMs and conversational AI platforms (Rasa, LLaMA-based models).
• Knowledge of data security standards and IT governance in government or regulated enterprise
  environments.

Qualifications

• B.Tech / M.Tech / M.Sc in Computer Science, AI/ML, Data Science, or related field.
  Relevant certifications in ML, MLOps, or cloud infrastructure are a plus.