Data Scientist

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 Junior Data Scientist & Agentic AI Developer to join our team. If you're excited to be part of a winning team, CirrusLabs () is a great place to grow your career. Experience - 3 to 5 years Location - Bengaluru Position Overview We are seeking a capable Data Scientist and Agentic AI Developer to independently design, develop, and evaluate intelligent AI agents. This role requires hands-on delivery of production-ready agentic systems with robust evaluation frameworks and measurable quality outcomes. Experience Required 3-5 years of professional experience in data science, machine learning, and AI development with demonstrated project delivery Key Responsibilities AI Agent Development & Delivery Independently design and develop production-grade agentic AI systems using Large Language Models Build and deploy multi-step reasoning workflows with tool orchestration Implement and optimize RAG (Retrieval-Augmented Generation) pipelines end-to-end Integrate external tools, APIs, and databases into functional agent systems Deliver scalable, reliable AI agents that meet performance benchmarks Own the complete development lifecycle from design to deployment Evaluation Framework Implementation Build comprehensive evaluation systems using LLM-as-a-judge methodologies Develop and deploy automated scoring pipelines for all quality metrics (correctness, helpfulness, coherence, relevance, simplicity, collaborativity) Implement RAGAs framework for factual accuracy and hallucination detection Create custom evaluator code for overall response quality assessment Deliver actionable evaluation reports with clear improvement recommendations Set up monitoring dashboards for real-time performance tracking Performance & Efficiency Optimization Monitor and optimize latency, throughput, and cost-per-interaction metrics Implement token usage optimization strategies to reduce operational costs Track and improve task completion rates and success metrics Analyze tool interaction efficiency and optimize workflows Deliver measurable improvements in agent response times and resource utilization Data Science & Analytics Delivery Conduct statistical analysis on agent performance data and user interactions Build and maintain automated reporting dashboards for stakeholders Design and execute A/B tests to validate improvements Analyze error patterns and implement corrective measures Deliver data-driven insights that drive product decisions Safety, Ethics & Compliance Implementation Implement bias detection systems and ensure fairness in outputs Build harmful content filtering and safety guardrails Develop and deploy compliance monitoring for EU AI Act, GDPR, HIPAA, DPDP standards Create radar chart visualizations for compliance metrics Document and maintain transparency, explainability, and human oversight measures Deliver audit-ready compliance reports Required Skills & Qualifications Technical Expertise (Must Have) Programming : Strong Python skills with production code experience; advanced SQL LLM Development : Proven experience building applications with GPT, Claude, or similar models Frameworks : Hands-on experience with LangChain, LangSmith, Phoenix, or equivalent agent frameworks Evaluation Tools : Experience implementing RAGAs or similar evaluation frameworks MLOps : Experience deploying ML models to production and monitoring performance APIs & Integration : Strong experience with REST APIs, webhooks, and system integration Vector Databases : Working knowledge of Pinecone, Weaviate, Chroma, or similar Proven Delivery Experience Track record of shipping AI/ML products or features to production Experience building end-to-end evaluation pipelines independently Demonstrated ability to optimize model performance and reduce costs Portfolio of completed projects with measurable business impact Experience working with observability and monitoring tools Domain Expertise Deep understanding of prompt engineering and LLM behavior optimization Knowledge of agentic architectures, tool calling, and multi-step reasoning Experience with conversational AI systems and dialogue management Understanding of information retrieval and RAG system design Familiarity with AI safety principles and alignment techniques Analytical & Problem-Solving Skills Strong debugging and troubleshooting capabilities Ability to analyze complex systems and identify root causes Data-driven decision making with statistical rigor Performance optimization mindset Proactive problem identification and resolution Professional Skills Self-driven with minimal supervision required Strong ownership mentality and accountability for deliverables Clear communication of technical concepts to non-technical stakeholders Ability to work under deadlines and manage multiple priorities Results-oriented with focus on business impact Required Tools & Technologies Must Have Experience With Frameworks : LangChain or LangGraph (production experience) Monitoring : LangSmith, Phoenix, or similar observability platforms LLM APIs : OpenAI, Anthropic, or Azure OpenAI Databases : PostgreSQL/MySQL + vector databases Cloud : AWS, Azure, or GCP deployment experience DevOps : Docker, CI/CD pipelines, Git workflows Should Be Comfortable With Python libraries: pandas, numpy, scikit-learn, matplotlib Evaluation frameworks: RAGAs, custom scoring systems Data visualization: Plotly, Streamlit, or Tableau API development: FastAPI or Flask Testing frameworks: pytest, unit testing, integration testing Work Environment & Expectations Independence Level Work autonomously on assigned features and improvements Make technical decisions within project scope Collaborate with product and engineering teams Escalate blockers proactively but resolve most issues independently Accountability Meet sprint commitments and delivery timelines Own quality of your deliverables end-to-end Participate in on-call rotation for production support Maintain high code quality and documentation standards Collaboration Work with product managers to understand requirements Partner with senior engineers on architecture decisions Share knowledge through documentation and team sessions Participate in code reviews and provide constructive feedback Preferred Qualifications Bachelor's or Master's in Computer Science, Data Science, or related field Experience with RLHF (Reinforcement Learning from Human Feedback) Experience with multi-modal AI systems Previous work in regulated industries (healthcare, finance,Logistics)