Forward Deployment Engineer

Tata Consultancy Services

Eden Prairie (MN)

On-site

USD 110,000 - 120,000

Full time

4 hours ago
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Benefits offered by this job

Discretionary Incentive
Medical Coverage: Medical & Health, D&
Dental & Vision
Parental Leaves
Auto & Home Insurance
Commuter Benefits
Certification & Training Reimbursement
Vacation & Holidays
401K Plan

Job summary

Tata Consultancy Services in the United States is seeking an experienced AI/ML & Forward Deployed Engineer with 8+ years of engineering expertise to deliver end-to-end AI/ML solutions. You will blend ML, software engineering, and stakeholder problem-solving to deploy production-grade, scalable, and secure systems aligned to business KPIs.

This role operates at the intersection of data, models, systems, and real users in fast-moving environments, with GenAI opportunities where applicable.

Qualifications

  • 8+ years of engineering experience in AI/ML.
  • Experience delivering production-grade AI/ML solutions.
  • Strong experience with GenAI/LLM engineering.
  • Proficient in building scalable, secure systems.
  • Knowledge of observability, governance and KPIs.

Responsibilities

  • Identify AI opportunities with stakeholders and define success metrics.
  • Lead workshops to assess feasibility, data readiness, and risks.
  • Prototype, pilot deployments and iterate based on user feedback.
  • Develop and productionize ML solutions (classification, NLP, forecasting).
  • Build and deploy RAG pipelines with grounding and guardrails.
  • Provide technical leadership and document architectures.

Skills

AI/ML Engineering
GenAI Engineering
MLOps
REST/gRPC APIs
Kubernetes
Docker
Data pipelines
Model evaluation
A/B testing
Guardrails design

Education

Bachelor's degree in CS

Tools

Docker
Kubernetes
CI/CD

Job description

Job Description
Role Overview

We are looking for an experienced AI/ML & Forward Deployed Engineer with 8+ years of engineering experience to deliver high-impact AI/ML (and GenAI, where applicable) solutions end-to-end. You will blend applied machine learning, software engineering, and stakeholder problem-solving to deploy production-grade systems that are scalable, secure, observable, and aligned to business KPIs.

This role is ideal for engineers who enjoy operating at the intersection of data + models + systems + real users, and who can thrive in ambiguous, fast-moving environments.

Key Responsibilities
  • Use-Case Discovery & Forward Deployment
  • Partner with stakeholders (business/product/customers) to identify and shape AI opportunities into well-defined use cases with success metrics, constraints, and rollout plans.
  • Run workshops and technical discovery to assess feasibility, data readiness, integration needs, and operational risks.
  • Drive rapid prototyping, pilot deployments, and iterative improvements based on real user feedback.
  • Applied ML Engineering (Classic ML + Deep Learning)
  • Develop and improve ML solutions (classification, regression, ranking, forecasting, anomaly detection, NLP).
  • Establish and maintain robust evaluation practices: offline metrics, validation strategies, experimentation, and A/B testing.
  • Perform feature engineering, error analysis, model optimization, and performance tuning for production requirements.
  • GenAI / LLM Engineering (If Applicable)
  • Build and productionize RAG (Retrieval-Augmented Generation) pipelines, including document ingestion, chunking strategy, embeddings, retrieval tuning, reranking, and response grounding.
  • Implement guardrails and reliability patterns: prompt templates, tool/function calling, hallucination reduction, citation strategies, and fallback paths.
  • Develop evaluation harnesses for GenAI: quality metrics, regression tests, safety tests, and human-in-the-loop workflows.
  • Productionization (MLOps / LLMOps)
  • Package models into scalable services and deploy using Docker/Kubernetes and CI/CD.
  • Implement model lifecycle management: model registry, versioning, automated retraining triggers, and governance workflows.
  • Build monitoring and observability: drift detection, latency/throughput monitoring, error tracking, alerting, and rollback mechanisms.
  • Systems Integration & Platform Collaboration
  • Build integration layers (REST/gRPC APIs, event-driven services) to embed AI capabilities into products and enterprise workflows.
  • Collaborate with data engineers to design reliable pipelines and ensure data quality, lineage, and governance.
  • Ensure secure and compliant design (PII/PHI handling, RBAC, secrets management, encryption, audit trails).
  • Technical Leadership & Enablement
  • Provide technical guidance and mentoring to eng ineers; lead design reviews and establish best practices.
  • Document solutions with architecture diagrams, runbooks, and operational playbooks.
  • Create reusable accelerators (templates, libraries, patterns) to scale deployments across teams or customers.
Salary Range: $110,000-$120,000 a year
TCS Employee Benefits Summary
  • Discretionary Annual Incentive.
  • Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
  • Family Support: Maternal & Parental Leaves.
  • Insurance Options: Auto & Home Insurance, Identity Theft Protection.
  • Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.
  • Time Off: Vacation, Time Off, Sick Leave & Holidays.
  • Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
Qualifications:

BACHELOR OF COMPUTER SCIENCE

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