Note: The job is a remote job and is open to candidates in USA. Centric Software is a global provider of AI-enabled product-concept-to-commercialization solutions for retailers, brands, and manufacturers. The Senior Frontier AI Deployment Engineer will lead the design and delivery of production-oriented generative AI solutions, translating ambiguous business needs into requirements and delivery plans. The role guides cross-functional and distributed teams, shapes AI architectures, oversees prototypes and production implementations, and defines evaluation, safety, and business-impact measures.
Responsibilities
- Lead discovery with business, product, data, security, and engineering stakeholders; convert ambiguous needs into clear use cases, requirements, acceptance criteria, risks, and delivery plans
- Act as the connective layer among teams in India, Europe, and North American Central and Pacific time zones, creating crisp decisions, handoffs, documentation, and follow-through
- Shape solution designs for retrieval-augmented generation (RAG), AI agents, tool use, orchestration, evaluation, guardrails, observability, and human-in-the-loop workflows
- Guide prototypes and production implementations, making pragmatic tradeoffs across user value, model quality, latency, cost, security, reliability, and maintainability
- Partner with engineers and architects on interfaces, data flows, integrations, deployment patterns, and operational readiness; contribute code or technical artifacts when it accelerates delivery
- Own stakeholder-facing demos and the supporting demo sites and environments, including setup, access, content and data readiness, reliability, presentation quality, and ongoing maintenance; lead stakeholder updates and technical workshops
- Define meaningful success measures and evaluation approaches for AI quality, safety, adoption, and business impact
- Stay current on rapidly changing AI capabilities and translate new developments into practical recommendations rather than technology for its own sake
Skills
- 6+ years of experience in software, data, ML/AI, solutions engineering, technical product delivery, or a closely related field
- Demonstrated senior-level ownership of ambiguous, cross-functional initiatives, including driving decisions and delivery across multiple phases rather than contributing only to isolated technical tasks
- Demonstrated delivery experience with at least one generative AI system, such as RAG, AI agents, copilots, semantic search, or LLM-enabled workflow automation. Candidates need not have built every component alone, but must clearly explain their contribution and the system's end-to-end behavior
- Excellent written, verbal, and visual communication, including the ability to explain technical choices to nontechnical stakeholders and business context to engineers
- Experience eliciting requirements, resolving ambiguity, prioritizing scope, defining acceptance criteria, and driving cross-functional execution
- Working knowledge of modern generative AI patterns: prompt and context design, embeddings and retrieval, agent/tool orchestration, model selection, evaluation, safety controls, observability, and production operations
- Ability to review architecture and code, troubleshoot across system boundaries, and produce lightweight prototypes or examples. Deep specialization in application coding is not required
- Experience collaborating across countries and time zones, with disciplined asynchronous documentation and handoffs
- Practical understanding of enterprise concerns including data privacy, security, access control, responsible AI, compliance, cost, and reliability
- Preferred location: Eastern (or) Central U.S. time zones, or a location with meaningful overlap across those hours. The role requires planned overlap with colleagues in India and Europe. Flexibility for occasional early or late meetings is expected; sustainable schedules and strong asynchronous practices are equally important
- Hands-on experience with AWS generative AI services, especially Amazon Bedrock and Amazon Bedrock AgentCore
- Experience in a forward-deployed, solutions architecture, technical program leadership, consulting, sales engineering, or product ownership role
- Experience establishing AI evaluation sets, quality metrics, red-team practices, guardrails, monitoring, or production feedback loops
- Familiarity with cloud-native architectures, APIs, event-driven systems, vector databases, identity and access management, and CI/CD
- Experience facilitating executive or customer-facing workshops and turning outcomes into an executable product or engineering backlog
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