Data Scientist & Agentic AI Developer

We are CirrusLabs . Our vision is to become the world's most sought-after niche digital transformation company that helps customers realize value through innovation. Our mission is to co-create success with our customers, partners and community. Our goal is to enable employees to dream, grow and make things happen. We are committed to excellence. We are a dependable partner organization that delivers on commitments. We strive to maintain integrity with our employees and customers. Every action we take is driven by value. The core of who we are is through our well-knit teams and employees. You are the core of a values driven organization.

You have an entrepreneurial spirit. You enjoy working as a part of well-knit teams. You value the team over the individual. You welcome diversity at work and within the greater community. You aren't afraid to take risks. You appreciate a growth path with your leadership team that journeys how you can grow inside and outside of the organization. You thrive upon continuing education programs that your company sponsors to strengthen your skills and for you to become a thought leader ahead of the industry curve.

You are excited about creating change because your skills can help the greater good of every customer, industry and community. We are hiring a talented Data Scientist & Agentic AI Developer to join our team. If you're excited to be part of a winning team, CirrusLabs ( http : / / www.cirruslabs.io ) is a great place to grow your career.

Experience - 5-8 years

Location - Bengaluru

Work Timings - 2pm - 11pm IST

Tech Stack : Python, LangChain, LangSmith, Phoenix, TensorFlow, PyTorch, OpenAI API, Anthropic Claude, Azure OpenAI, AWS / Azure / GCP. We value innovation, collaboration, and a commitment to ethical AI development.

Position Overview

We are seeking an experienced Data Scientist and Agentic AI Developer to design, develop, and evaluate intelligent AI agents that deliver high-quality, reliable, and compliant solutions. This role requires a blend of data science expertise, AI / ML engineering capabilities, and hands-on experience building agentic systems.

Experience Required

5-6 years of professional experience in data science, machine learning, and AI development

Key Responsibilities

AI Agent Development & Deployment

Design and develop agentic AI systems powered by Large Language Models (LLMs) with tool-calling capabilities

Build and optimize multi-step reasoning workflows and agent orchestration frameworks

Implement retrieval-augmented generation (RAG) pipelines for knowledge-intensive applications

Integrate external tools, APIs, and databases into agent workflows

Deploy and monitor production-grade AI agents at scale

Evaluation & Quality Assurance

Develop comprehensive evaluation frameworks using LLM-as-a-judge methodologies

Implement automated scoring systems for output quality metrics (correctness, helpfulness, coherence, relevance)

Design and execute robustness testing including adversarial attack scenarios

Monitor and reduce hallucination rates and ensure factual accuracy

Track performance metrics including latency, throughput, and cost-per-interaction

Data Science & Analytics

Analyze agent performance data to identify improvement opportunities

Build custom evaluation pipelines and scoring rubrics

Conduct A / B testing and statistical analysis for model optimization

Create dashboards and visualization tools for stakeholder reporting

Implement RAGAs (Retrieval Augmented Generation Assessment) frameworks

Safety, Ethics & Compliance

Ensure AI systems meet ethical standards including bias detection and fairness

Implement safety guardrails to prevent harmful content generation

Develop compliance monitoring systems for regulatory frameworks (EU AI Act, GDPR, HIPAA, DPDP)

Document transparency and explainability measures

Establish human oversight protocols

Required Skills & Qualifications

Technical Expertise Programming : Strong proficiency in Python; experience with AI / ML frameworks (Lang Chain, Lang Smith, Phoenix, or similar)

LLM Expertise : Hands-on experience with GPT, Claude, or other frontier models; prompt engineering and fine-tuning

Machine Learning : Deep understanding of NLP, deep learning architectures, and model evaluation

Tools & Platforms : Experience with MLOps tools, vector databases, and observability platforms

Data Engineering : Proficiency in SQL, data pipelines, and ETL processes

Domain Knowledge

Understanding of agentic AI architectures and autonomous systems

Knowledge of RAG systems and information retrieval techniques

Familiarity with LLM evaluation methodologies and benchmarks

Experience with conversational AI and dialogue systems

Understanding of AI safety, alignment, and interpretability

Evaluation & Metrics

Experience designing evaluation rubrics and scoring systems

Proficiency with automated evaluation frameworks (RAGAs, custom evaluators)

Understanding of quality metrics : coherence, fluency, factual accuracy, hallucination detection

Knowledge of performance metrics : latency optimization, token usage, throughput analysis

Experience with user experience metrics (CSAT, NPS, turn count analysis)

Soft Skills Strong analytical and problem-solving abilities

Excellent communication skills for cross-functional collaboration

Ability to balance innovation with practical constraints

Detail-oriented with a focus on quality and reliability

Self-driven with ability to work in fast-paced environments

Preferred Qualifications

Experience with compliance frameworks and regulatory requirements

Background in conversational AI or chatbot development

Knowledge of reinforcement learning from human feedback (RLHF)

Experience with multi-modal AI systems

Tools & Technologies Frameworks : Lang Chain, Lang Smith, Phoenix, TensorFlow, PyTorch

LLM Platforms : OpenAI API, Anthropic Claude, Azure OpenAI

Databases : Vector databases (Pinecone, Weaviate, Chroma), PostgreSQL, MongoDB

Monitoring : Lang Smith, Phoenix, custom observability tools

Cloud : AWS / Azure / GCP experience preferred

Version Control : Git, CI / CD pipelines

What You'll Deliver Production-ready agentic AI systems with measurable quality improvements

Comprehensive evaluation frameworks with automated scoring

Performance dashboards and reporting systems

Documentation for technical specifications and compliance standards

Continuous improvement strategies based on data-driven insights