Tech Specialist

Job Description

Skill Set

• Claude with Amazon Bedrock

• Total Experience :

• 8.00 to 10.00 Years

• No of Openings :

• 1

• Job Post Date :

• 03/07/2026

• Job Expiry Date :

• 31/08/2026

• Domain :

• IT

• Location :

• PLANO [United States]

• Job Reference No :

• 4094363

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• Job Summary

• Tittle : AI Architecture

• Location: Dallas TX (Day 1 onsite)

• Overview

• We are seeking a seasoned AI Architect who combines deep technical expertise with the ability to articulate and sell AI solutions to enterprise stakeholders. This is a hybrid role requiring both architectural rigor and strong communication skills—someone who can inspire confidence in the boardroom and lead engineering teams in the field.

• Critically, we are looking for someone with genuine hands-on implementation experience—an architect who not only designs AI solutions but has actually built and deployed them end-to-end. We value the full journey: from initial discovery and solution design, through proof-of-concept, to production deployment and ongoing optimization.

The ideal candidate brings fluency across generative AI, agentic AI, and traditional machine learning, with enterprise depth in defining architectures that span orchestration layers, model selection, data integration, and governance. They understand AI both as a disruptive force—enabling entirely new business models—and as an infusion capability, embedding intelligence into existing enterprise systems and workflows.

Key Responsibilities

Design and define enterprise-scale AI architectures, integrating AI through both disruptive innovation and intelligent infusion into existing business systems and platforms

Architect multi-layered AI solutions spanning agent orchestration frameworks, MCP (Model Context Protocol) servers, LLM integrations, RAG pipelines, and supporting data infrastructure

Evaluate and select appropriate AI technologies, models, frameworks, and cloud services based on business requirements, cost, and governance constraints

Lead pre-sales and solution design engagements—translating complex AI concepts into compelling business value propositions for executive and technical audiences

Develop solution strategies with clear ROI narratives; actively participate in customer-facing presentations, RFP responses, and solution workshops

Own the complete solution lifecycle from whiteboard to production—providing architectural leadership through design, development, testing, and deployment phases

Guide and support implementation teams with hands-on experience, solving real-world engineering challenges as they arise in production environments

Define standards, patterns, and best practices for AI architecture across the organization and with external partners

Mentor and upskill technical teams in agentic AI design, multi-model integration, prompt engineering, and responsible AI practices

Stay current with the rapidly evolving AI landscape—evaluating emerging models, tools, and frameworks and advising on adoption strategy

Required Experience

8+ years in enterprise software architecture, with at least 3+ years focused on AI/ML solutions at scale

Deep knowledge of generative AI, agentic AI systems, and traditional machine learning, including:

Large Language Models (LLMs) – selection, fine-tuning, prompt engineering, and lifecycle management

Agentic AI design – agent orchestration, tool use, multi-agent coordination, and MCP server configuration

RAG (Retrieval-Augmented Generation) – vector databases, embedding models, document grounding, and hybrid search

Traditional ML – supervised/unsupervised learning, model training pipelines, and MLOps practices

Hands-on multi-model experience—selecting, integrating, and orchestrating frontier and open-source models including:

Anthropic Claude (e.g., Claude Sonnet, Claude Opus) for reasoning and complex language tasks

OpenAI GPT series for generative and agentic use cases

Google Gemini for multimodal and large context window applications

Meta Llama and other open-source models for on-premise or cost-optimized deployments

Ability to benchmark, evaluate, and select the right model for the right task in a production context

Proven experience with major cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI) and associated infrastructure services

Experience integrating AI solutions with enterprise platforms such as Salesforce, SAP, ServiceNow, Microsoft 365, or similar

Demonstrated track record of successfully translating AI architectures into delivered, production-grade solutions

Strong pre-sales capability—experience leading solution workshops, responding to RFPs, and presenting to senior decision-maker

Technical Competencies

Enterprise AI architecture patterns and multi-layered solution design

Agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, watsonx Orchestrate) and MCP protocol-based integrations

Prompt engineering, chain-of-thought reasoning, and advanced LLM interaction patterns

Vector databases (e.g., Pinecone, Weaviate, pgvector, Chroma) and semantic search architecture

Cloud-native and hybrid deployment architectures across AWS, Azure, GCP, and on-premise environments

API design, microservices, event-driven architecture, and enterprise system integration patterns

AI governance, responsible AI frameworks, model risk management, bias detection, and explainability

AI observability and monitoring—model drift detection, performance tracking, data quality, and inference health

Data architecture, data pipelines, and governance in the context of AI workloads

Security and compliance considerations for enterprise AI deployments

Soft Skills & Leadership Qualities

Exceptional communication and presentation skills—able to engage C-suite executives, business stakeholders, and deep technical teams with equal confidence

Strong sales acumen and solution storytelling ability—can craft a compelling narrative around AI value and guide customers through complex solution decisions

Strategic thinker with a consistent focus on business outcomes over technical novelty

Proven ability to lead through influence in matrixed enterprise environments without direct authority

Comfortable navigating ambiguity and driving clarity—from early-stage concept to production delivery

Confident public speaker—comfortable presenting at customer briefings, industry events, and executive forums

Collaborative and empathetic leader—able to mentor, inspire, and upskill diverse technical teams

Nice to Have

Relevant AI/cloud certifications (AWS Certified Machine Learning, Azure AI Engineer, Google Professional ML Engineer, or equivalent)

Experience with AI governance platforms and model observability tooling (e.g., Fiddler, Arize, Arthur AI, or similar)

Background in enterprise consulting, solution architecture, or pre-sales engineering roles

Published thought leadership—blog posts, whitepapers, conference presentations, or open-source contributions in the AI space

Experience scaling AI solutions across multiple business units or global enterprise environments

Exposure to regulated industries (financial services, healthcare, government) where AI governance and compliance are mission-critical

Familiarity with AI safety, alignment principles, and emerging regulatory frameworks (EU AI Act, NIST AI RMF)

The pay range for this role is $140k - $150k per annum including any bonuses or variable pay . Tech Mahindra also offers benefits like medical, vision, dental, life, disability insurance and paid time off (including holidays, parental leave, and sick leave, as required by law). Ask our recruiters for more details on our Benefits package. The exact offer terms will depend on the skill level, educational qualifications, experience, and location of the candidate.

Tech Mahindra is an Equal Employment Opportunity employer. We promote and support a diverse workforce at all levels of the company. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, age, national origin or disability. All applicants will be evaluated solely on the basis of their ability, competence, and performance of the essential functions of their positions with or without reasonable accommodations. Reasonable accommodations also are available in the hiring process for applicants with disabilities. Candidates can request a reasonable accommodation by contacting the company ADA Coordinator at ADA_Accomodations@TechMahindra.com .”

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