Senior Specialist - Data Sciences
Houston - Texas - USAOn-siteFull-timeData & Analytics
Description
Gen AI Architect Role Type Technical leadership architecture design hands-on implementation platform engineering through field collaboration LTM is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine how they operate compete and grow By combining deep domain knowledge advanced engineering and transformation expertise LTM helps clients navigate their most complex challenges and seize new opportunities in an increasingly digital world BlueVerse is LTMs Enterprise AI business unit purposebuilt to help organizations move beyond pilots into scaled productiongrade AI adoption BlueVerse blends AI strategy functional consulting an AI Foundry and agentic AI platforms to deliver integrated solutions that transform how work gets done across the enterprise Operating across Banking Insurance Manufacturing Retail CPG Energy Utilities Travel Hospitality Hi Tech and Media BlueVerse works closely with industry GTM teams to create repeatable AI solutions accelerators and transformation blueprints Role Overview The Gen AI Architect is responsible for designing and operationalizing enterprisegrade Gen AI capabilities within BlueVerse This role architects productionready AI solutions that combine LLM reasoning retrieval orchestration and enterprise controls to deliver trustworthy business outcomes in real operating environments You will work across architecture product and engineering teams to move Gen AI features from concept to robust implementation with emphasis on quality safety performance maintainability and clear operational ownership The role is both foundational and executionoriented setting strong architectural patterns while helping teams implement them in ways that are observable testable and resilient under production constraints You will collaborate with field and client-facing teams to shape highvalue use cases build rapid proofsofvalue and convert successful pilots into productionready MVP plans that move from rapid proofofvalue to scalable enterprise rollout with strong governance observability and measurable business impact
Key Responsibilities
Gen AI Architecture and Design
Design solution patterns for enterprise Gen AI use cases including copilots autonomous task agents decision support systems and workflow automation across multiple business domains
Define architecture for model routing prompt strategy grounding memory handling and tool orchestration with explicit design choices for reliability and cost control
Establish patterns for secure integration of enterprise data APIs and workflow systems into Gen AI applications without compromising governance and data boundaries
Ensure designs support explainability policy enforcement and operational observability so teams can diagnose and improve behavior continuously
Productionization and Quality
Build and guide implementation of evaluation frameworks for accuracy relevance safety hallucination control latency and consistency across release cycles Partner with platform engineering to standardize reusable components for prompt templates guardrails telemetry fallback logic and controlled rollout mechanisms Create practical evaluation harnesses for task success policy compliance toolcall reliability and costlatency tradeoffs to compare baseline versus PoV improvements Contribute to performance and cost optimization across model and infrastructure choices through benchmarkdriven architecture decisions Create reference implementations that can be reused across domains and client deployments reducing setup time and implementation risk Fieldto Platform Execution Partner with client-facing and delivery teams to translate business problems into measurable outcome hypotheses and technically feasible thinslice PoV scopes Define agentic blueprints covering agent roles orchestration patterns knowledge strategy guardrails observability and humanintheloop escalation Produce clean handoffs to delivery squads with MVP backlogs architecture decisions and production controls such as identity audit logging and fallback design Design for enterprise integration across client ecosystems and major platforms while preserving security privacy and compliance boundaries Governance and Enablement Embed responsible AI and governance controls into architecture patterns from day one including traceability guardrail coverage and intervention pathways Support risk and compliance teams with design artifacts required for enterprise approvals audits and production readiness reviews Document technical standards and best practices for Gen AI development across BlueVerse teams and keep them current with platform evolution Mentor engineers and solution teams on scalable Gen AI architecture approaches through design reviews and practical implementation guidance
Requirements
Mandatory Skills : Python