Senior Data Scientist at TriNet in Hyderabad

Job description

TriNet is a leading provider of comprehensive human resources solutions for small to midsize businesses (SMBs). We enhance business productivity by enabling our clients to outsource their HR function to one strategic partner and focus on operating and growing their core businesses. Our full-service HR solutions include payroll processing, human capital consulting, employment law compliance and employee benefits, including health insurance, retirement plans and workers’ compensation insurance. TriNet has a nationwide presence and an experienced executive team. Our stock is publicly traded on the NYSE under the ticker symbol TNET. If you are passionate about innovation and making an impact on the large SMB market, join us as we power our clients’ business success with extraordinary HR. Do not meet every single requirement? Studies have shown that many potential applicants discourage themselves from applying to jobs unless they meet every single requirement. TriNet always strives to hire the most qualified candidate for a particular role, ensuring we deliver outstanding results for our small and medium-size customers. So if you're excited about this role but your past experience doesn't align perfectly with every single qualification in the job description, nobody’s perfect – and we encourage you to apply. You may just be the right candidate for this or other roles. A Brief Overview: This is a high-impact, execution-focused role responsible for building and delivering AI-powered agents and agentic workflows that address critical business challenges. The role combines strong applied data science foundations with hands-on delivery using commonly used technology ecosystems, including Anthropic Claude on AWS Bedrock, Claude Code, Microsoft Copilot, GitHub Copilot and related frameworks and observability tools. You will partner with Data & Analytics leaders and cross-functional teams to design and deliver scalable, secure, and compliant AI solutions in enterprise environments. This role is ideal for someone who excels at translating business needs into clear requirements and delivering high-quality AI agents that operate reliably within real-world workflows. Key Responsibilities: Agentic AI Solution Design and Delivery Lead the design, development and testing of single-agent and multi-agent solutions using LLMs, prompt and context engineering, retrieval-augmented generation (RAG), tool use and structured outputs. Translate business problems into agent goals, workflow logic, system interactions, acceptance criteria, exception handling and human-in-the-loop controls. Integrate agents with enterprise platforms, APIs, MCP servers, databases, SaaS applications and governed data sources to enable secure end-to-end workflow execution. Build and optimise retrieval, grounding, memory and orchestration patterns that improve accuracy, traceability and task completion. Establish evaluation and observability practices covering quality, groundedness, safety, latency, cost, failure modes and regression testing. Productionise solutions through source control, automated testing, deployment, release validation, monitoring, issue triage and continuous optimisation. Applied Data Science and Machine Learning Frame business problems as analytical, statistical, machine learning or agentic AI use cases, selecting the simplest effective approach. Prepare structured and unstructured data and perform feature engineering, model development, validation and error analysis using reproducible Python and SQL workflows. Design experiments and measurement approaches to demonstrate model performance, incremental value and business impact. Collaboration, Governance and Leadership: Partner with Product, Engineering, Security, Legal, Compliance and business teams to define priorities, dependencies, controls and acceptance criteria. Embed responsible AI practices, including access controls, privacy protections, guardrails, human oversight, fallback mechanisms and audit-read