Senior Specialist - Data Sciences

Role description

Job Summary

Required Qualifications

Must Have:

Strong software engineering fundamentals and proficiency in Python plus Java Go TypeScript is a strong plus

Experience of working with Codex.

Proven experience building LLM powered applications in production tool calling function, calling structured outputs retrieval and evaluation.

Experience designing distributed systems and APIs REST, RPC plus event driven patterns Kafka, SQS, Pub Sub.

Solid understanding of data engineering basics SQL data modeling feature engineering and data quality

Handson knowledge of cloud platforms AWS or Azure or GCP containers, Docker and orchestration Kubernetes preferred.

Ability to write clean testable secure code comfortable with code reviews and engineering rigor

Experience with multiagent systems planning verification and autonomous workflow execution

Experience with vector databases hybrid search and knowledge graphs

Familiarity with model evaluation offline evals golden datasets adversarial testing regression harnesses and AB testing.

 

Technical Skills:

Agent frameworks Lang Graph Semantic Kernel similar orchestration frameworks or equivalent custom implementations

RAG tooling embedding pipelines hybrid retrieval reranking chunking strategies citation provenance

Observability Open Telemetry structured logging dashboards ing

Data systems OLTP analytics warehouses lakes streaming pipelines feature stores optional

Testing unit integration tests for tools replay tests for agent traces eval harnesses for LLM outputs

 

 Key Responsibilities:

1. Agentic AI System Design Engineering

Design and implement agent architectures planner executor tool using agents multiagent orchestration reflection evaluation loops.

Build tooling integrations for agents merchant systems underwriting platforms transaction stores risk engines CRM case tools knowledge bases and workflow engines.

Implement robust state management session memory task plans provenance traceability and replay ability of agent actions

 

2. LLM RAG Engineering for Payments Workloads

Develop RAG pipelines over policies SOPs card network rules underwriting guidelines dispute playbooks and merchant agreements.

Apply prompt and system design structured output patterns and schema validation for deterministic agent behaviour.

Optimize for latency cost and reliability using caching model routing and evaluation driven prompt iteration.

 

3. ML Decisioning Integration

Combine LLM agents with classical ML models fraud scoring anomaly detection risk scoring and rules engines.

Build feedback loops from outcomes chargeback win rate false positives approval uplift to continuously improve models and agent strategies.

 

4. Safety Compliance and Responsible AI

 

Implement guardrails PII handling policy enforcement prompt injection defences tool per missioning rate limiting and safe failover.

Ensure auditability why an agent took action evidence used and human approval where required humanintheloop.

 

5. Product ionization MLOps LLMOps

Build CICD for agent services evaluation suites telemetry drift detection and incident response playbooks.

Instrument agent behavior using tracing spans structured logs and metrics task success tool errors hallucination indicators

 

6. Collaboration Leadership 

Partner with Product Risk Ops Underwriting Compliance and Engineering to convert business problems into deployable AI solutions.

Mentor engineers set standards for agent design patterns testing and production readiness.

Other details

Benefits/perks listed below may vary depending on the nature of your employment with LTIMindtree (“LTIM”):

Benefits and Perks:

• Comprehensive Medical Plan Covering Medical, Dental, Vision


• Short Term and Long-Term Disability Coverage


• 401(k) Plan with Company match


• Life Insurance


• Vacation Time, Sick Leave, Paid Holidays


• Paid Paternity and Maternity Leave

The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay and other forms of bonus or variable compensation.

Disclaimer: The compensation and benefits information provided herein is accurate as of the date of
this posting.

LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our
employment decisions are made without regard to race, color, creed, religion, sex (including
pregnancy, childbirth or related medical conditions), gender identity or expression, national origin,
ancestry, age, family-care status, veteran status, marital status, civil union status, domestic
partnership status, military service, handicap or disability or history of handicap or disability, genetic
information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation
or preference, or any other characteristic protected by applicable federal, state, or local law, except
where such considerations are bona fide occupational qualifications permitted by law.