AIML Engineer

Darwinbox Digital Solutions Pvt. Ltd.; Pune District; On-site; INR 2,600,000 - 3,800,000; Full time

Job summary

Darwinbox Digital Solutions Pvt. Ltd. in Pune seeks a Senior/Lead AI/ML Engineer with 6+ years of AI/ML delivery experience, focusing on Generative AI and modern cloud workflows. You will own end-to-end solution delivery, mentor juniors, and steer projects from design through deployment and monitoring.

You will leverage MCP, RAG, LangChain, and advanced prompting to build scalable AI systems, with emphasis on production-grade observability and cost-efficient deployment.

Qualifications

• 6+ years of experience in AI/ML solution development and deployment.
• Proven track record of end-to-end ownership of AI/ML projects.
• Strong programming skills in Python and SQL.
• Hands-on experience with Generative AI, LLMs, RAG, LangChain, MCP, and orchestration frameworks.
• Deep understanding of ML algorithms, statistical methods, and embeddings.
• Experience with cloud-native AI/ML workflows (Vertex AI, BigQuery, Dataflow, Cloud Functions).
• Strong grasp of MLOps pipelines: CI/CD, monitoring, and retraining workflows.
• Demonstrated experience mentoring and guiding junior engineers.
• Knowledge of Docker/Kubernetes for deployment and containerization.

Responsibilities

• Lead the design, training, and optimization of AI/ML and Generative AI models.
• Build and oversee conversational AI solutions, chatbots, and agents using LangChain and RAG.
• Define architecture choices, trade-offs, and deployment strategies.
• Review and validate deliverables from junior engineers.
• Oversee large-scale datasets for AI/ML applications, ensuring quality and normalization.
• Define scalable and reliable data engineering workflows.
• Mentor junior team members in data preprocessing, feature engineering, and analysis.
• Lead deployment and optimization of AI/ML workflows on cloud platforms (preferably GCP).
• Ensure production-grade scalability, observability, and retraining pipelines.
• Implement cost-efficient and secure deployment strategies.
• Guide, mentor, and coach junior engineers in coding, debugging, and design reviews.
• Build a collaborative team environment that encourages learning.

Skills

Python

SQL

Generative AI

LLMs

MLOps

Cloud platforms

LangChain

Mentoring

Leadership

Docker

Kubernetes

Education

Bachelor’s or Master’s in CS/CE

Tools

BigQuery

Vertex AI

Dataflow

Kubernetes

Docker

Job description

Experience Level: 6+ years Location: [Pune] Type: Full-Time

Job Summary

We are looking for a highly skilled and motivated Senior/Lead AI/ML Engineer with expertise in Generative AI and hands-on experience in GCP or other cloud platforms. The ideal candidate will have a proven track record of end-to-end project delivery , including design, development, deployment, and monitoring of AI/ML solutions.

In this role, you will take ownership of solution delivery , guide and mentor junior team members, and ensure high-quality, production-ready outcomes. You will leverage advanced frameworks such as MCP, Retrieval-Augmented Generation (RAG), and REACT to build scalable AI/ML systems and play a key role in driving innovation within the organization.

Lead the design, training, and optimization of AI/ML and Generative AI models.

Build and oversee conversational AI solutions, chatbots, and agents using LangChain, RAG, and advanced prompting.

Define architecture choices, trade-offs, and deployment strategies.

Review and validate deliverables from junior engineers.

Oversee large-scale datasets for AI/ML applications, ensuring quality, transformation, and normalization.

Define scalable and reliable data engineering workflows.

Mentor junior team members in data preprocessing, feature engineering, and analysis.

Lead deployment and optimization of AI/ML workflows on cloud platforms (preferably GCP: Vertex AI, BigQuery, Dataflow).

Ensure production-grade scalability, observability, and retraining pipelines .

Implement cost-efficient and secure deployment strategies.

Guide, mentor, and coach junior engineers in coding, debugging, and design reviews.

Build a collaborative team environment that encourages learning and innovation.

Provide technical direction, ensuring adherence to best practices and delivery timelines.

5. Stakeholder Collaboration

Act as a bridge between business stakeholders and the technical team.

Translate business requirements into technical roadmaps.

Communicate risks, trade-offs, and progress clearly to leadership and clients.

Stay updated with the latest in Generative AI, LLMs, agent orchestration frameworks, and advanced ML techniques.

Evaluate and adopt new technologies to enhance solutions.

Proactively recommend improvements in architecture, processes, and delivery.

Required Skills & Qualifications

6+ years of experience in AI/ML solution development and deployment.

Proven track record of end-to-end ownership of AI/ML projects .

Strong programming skills in Python and SQL.

Hands-on experience with Generative AI, LLMs, RAG, LangChain, MCP, and orchestration frameworks .

Deep understanding of ML algorithms, statistical methods, and embeddings.

Experience with cloud-native AI/ML workflows (Vertex AI, BigQuery, Dataflow, Cloud Functions).

Strong grasp of MLOps pipelines : CI/CD, monitoring, and retraining workflows.

Demonstrated experience mentoring and guiding junior engineers.

Knowledge of Docker/Kubernetes for deployment and containerization.

Preferred Skills

Familiarity with Reinforcement Learning from Human Feedback (RLHF) .

Exposure to AI governance, compliance, and security best practices .

Experience leading small-to-medium teams in delivery-focused environments.

Knowledge of cost optimization strategies in cloud AI solutions.

Hands-on with advanced agent frameworks (e.g., REACT, Agent-to-Agent orchestration).

Key Attributes

Strong analytical, debugging, and problem-solving skills.

Leadership, accountability, and ownership mindset.

Ability to mentor and uplift junior engineers while meeting deadlines.

Excellent communication skills with both technical and non-technical stakeholders.

Proactive learner with the ability to adapt quickly to new technologies.