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CAI AI Solution & Integration Owner in REMOTE, India

AI Solution & Integration Owner

Req number:

R7298

Employment type:

Full time

Worksite flexibility:

Remote

Who we are

CAI is a global services firm with over 9,000 associates worldwide and a yearly revenue of $1.3 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.

Job Summary

We are seeking a highly skilled AI solution architect to join our dynamic team. As an AI Solution Architect, you will play a crucial role in Design and deliver the end-to-end AI solution architecture, including model behavior, evaluation, integration, deployment, reliability, and cost - so the solution (or agent) is correct, safe, scalable, and operationally sustainable. This position will be full-time and Hybrid.

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Job Description

We are seeking an AI Solution Architect who can Design and deliver the end-to-end AI solution architecture. This position will be Full-time and Hybrid position.

What You’ll Do

End-to-End Solution Architecture

  • Select solution patterns: classical ML vs LLM vs hybrid, retrieval-augmented generation (RAG), orchestration, AI agents (if appropriate).

  • Define system architecture: APIs, services, event flows, data interfaces, identity and access.

  • Define non-functional requirements: latency, availability, scalability, resilience.

Model Behavior, Quality & Evaluation (explicit ownership)

  • Own model/prompt behavior and quality: define evaluation strategy and acceptance thresholds.

  • Implement evaluation: offline tests, golden datasets, regression testing for prompts/models.

  • Own error analysis and failure mode mitigation (hallucinations, bias, data leakage, prompt injection risks).

  • Define “safe completion” behavior for GenAI: guardrails, filters, and escalation paths.

Integration & Deployment Ownership

  • Build/oversee integration into TE’s applications and business workflows.

  • Own the deployment approach (CI/CD, environment configuration, secrets, feature flags).

  • Ensure observability: logging, metrics, tracing, model/prompt versioning.

Security, Privacy, Compliance-by-Design (technical)

  • Ensure proper data handling, encryption, access controls, and least privilege.

  • Ensure compliance requirements translate into technical controls (e.g., retention, PII handling).

Key Deliverables

  • Solution architecture (HLD/LLD), interface contracts, integration plan

  • Model/prompt strategy and evaluation plan (metrics, thresholds, test suites)

  • MVP/pilot reference implementation + production deployment design

  • Monitoring dashboards: latency, cost, errors, quality signals

  • Runbooks: incident response, rollback plan, version management

  • Security & privacy technical design notes (controls, data paths)

Decision Rights (owns the call)

  • Technical architecture and build-vs-buy decisions (within agreed governance and project-lead)

  • Model/prompt selection and evaluation gates for release readiness

  • Integration approach and production readiness from a technical standpoint

Key Interfaces

  • Collaborate with application owners / platform teams (cloud, DevOps, endpoint teams)

  • Security engineering, IAM, network teams

  • Data role training data, quality, lineage, and governance

  • Business SMEs for evaluation scenarios and acceptance tests

What You'll Need

Required

Bachelor degree: Computer Science, Software Engineering, Data Science, Artificial Intelligence / Machine Learning, Applied Mathematics or Engineering (with strong CS content)

QUALIFICATIONS & EXPERIENCE

Artificial Intelligence & Machine Learning

Model evaluation techniques (precision/recall, ROC, grounding metrics)

Overfitting, generalization, bias, and robustness

Understands LLM concepts:

  • Prompt engineering

  • Fine‑tuning vs prompt‑only approaches

  • Failure modes (hallucination, prompt injection)

Software Architecture & Engineering

  • Distributed systems concepts

  • API design and integration patterns

  • Microservices, event‑driven architectures

  • Observability (logging, metrics, tracing

3+ years of overall experience

Reasonable accommodation statement

If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.

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