AI Engineer

Role: AI Engineer

About Sutra.AI

AI Enterprise SaaS Platform

Our mission is to help enterprises transform raw data into intelligent, actionable insights through AI, automation, and decision intelligence.

Role Summary

AI Engineer

The ideal candidate is hands-on, detail-oriented, and thrives in a fast-paced environment where ideas move quickly from prototype to production.

You will collaborate closely with the AI Productization, Data, and Engineering teams to design, develop, and optimize intelligent systems that power Sutra’s next-generation AI capabilities.

Why This Role Matters

AI lies at the heart of Sutra.AI’s mission.

complex business problems

model, LLM workflow, and intelligent agent

production-grade capabilities

Must-Have Qualifications

• Bachelor’s or Master’s degree in

  Computer Science, Data Science, AI/ML, or related disciplines

  .

• 3–4 years

  of hands-on experience in

  AI/ML, LLMs, or Generative AI

  application development.
• Experience with

  RAG (Retrieval-Augmented Generation)

  and

  Agentic Frameworks

  .
• Prior experience

  fine-tuning models

  (OpenAI, LLaMA, Mistral, Falcon, etc.) preferred.

• Portfolio or GitHub

  showcasing AI or GenAI projects.

Key Responsibilities

1. AI/ML Model Development

• Build and optimize supervised and unsupervised ML models using

  Python and Scikit-Learn

  .
• Perform

  feature engineering, data wrangling, and model evaluation

  for structured and unstructured datasets.
• Apply

  evaluation metrics

  (ROC-AUC, F1, RMSE, Precision, Recall) for benchmarking.
• Collaborate with Data and Engineering teams to ensure

  reproducibility and deployment readiness

  .

2. Generative AI & LLM Engineering

• Develop and integrate

  LLM-based applications

  using

  LangChain, Autogen, or LangGraph

  .
• Perform

  fine-tuning and instruction-tuning

  using

  Hugging Face Transformers, PEFT, LoRA, or OpenAI APIs

  .
• Optimize

  prompts, model parameters, and responses

  for factual accuracy and contextual relevance.
• Implement

  RAG pipelines

  using

  Pinecone, FAISS, Chroma, or Weaviate

  .
• Build

  evaluation pipelines

  to assess LLM output quality, coherence, and bias.

3. AI Agent Development

• Design and deploy

  autonomous AI agents

  capable of reasoning, planning, and multi-step tool use.
• Leverage frameworks such as

  LangGraph, Autogen, or CrewAI

  for

  multi-agent systems

  .
• Integrate agents with

  APIs, databases, and internal platforms

  to automate workflows.
• Enhance

  reliability, scalability, and maintainability

  of deployed AI systems.

4. Continuous Improvement & Documentation

• Maintain

  comprehensive documentation

  and model tracking for reproducibility.
• Collaborate with cross-functional teams for

  smooth integration

  into customer solutions.
• Participate in

  peer reviews and sprint retrospectives

  to ensure quality and delivery efficiency.
• Research and adopt

  emerging AI/ML and agentic advancements

  to strengthen Sutra’s AI stack.

Core Technical Competencies

Programming:

Databases:

LLM / GenAI Frameworks:

Fine-Tuning Techniques:

Evaluation & Optimization:

Vector Databases:

Bonus Tools:

Soft Skills

• Deep curiosity and passion for emerging AI technologies.
• Clear, structured communication and documentation ability.
• Ability to

  translate technical outcomes

  for non-technical audiences.
• Strong ownership, accountability, and commitment to delivery timelines.
• Collaborative mindset and comfort in agile, cross-functional teams.

Success Metrics

• Model Accuracy & Quality:

  Achieves or exceeds benchmark accuracy and consistency.

• LLM Fine-Tuning Impact:

  Demonstrated improvement in model performance post-tuning.

• Delivery Timeliness:

  On-time completion of key milestones and deliverables.

• Documentation Completeness:

  Clear, reproducible code and experiment logs.

Role Logistics

Location:

Reporting To:

Cadence & Collaboration: