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You will be responsible for owning the design and implementation of scalable, multi-step reasoning and agent-based workflows using the firms AI framework to build platform services, pipelines, and developer tooling. You will collaborate with the central AI team to translate framework releases into stable platform capabilities, working across platform teams and third-party vendors to deliver production-grade solutions. Your role will involve designing workflows that incorporate retrieval-augmented generation (RAG) across structured and unstructured data, implementing guardrails, validation layers, and hallucination-mitigation techniques aligned with the standards defined in the firm. You will translate business problems into impactful solutions incorporating automation across tools and workflows. Additionally, you will serve as the primary code-level reviewer for the AI systems and frameworks and define and enforce technology roadmaps, best practices, strategies, and standards for AI adoption across the organization. Your contribution will also be crucial in commoditizing AI by incorporating it into existing systems (front-end and back-end apps) and ensuring solution quality across performance, scalability, security, cost efficiency, and responsible AI considerations. Moreover, you will mentor and coach junior engineers on advanced AI techniques, best practices, and design. Key Responsibilities: - Own the design and implementation of scalable, multi-step reasoning and agent-based workflows - Collaborate with the central AI team to translate framework releases into stable platform capabilities - Design workflows incorporating retrieval-augmented generation (RAG) across structured and unstructured data - Implement guardrails, validation layers, and hallucination-mitigation techniques - Translate business problems into impactful solutions incorporating automation - Serve as the primary code-level reviewer for the AI systems and frameworks - Define and enforce technology roadmaps, best practices, strategies, and standards for AI adoption - Contribute to commoditizing AI by incorporating it into existing systems - Mentor and coach junior engineers on advanced AI techniques, best practices, and design Qualifications Required: - Proficiency in Python, with strong experience in machine learning frameworks such as TensorFlow and PyTorch - Familiarity with data manipulation libraries such as Pandas and NumPy - Experience working with Spec-driven engineering (SDD) and structured problem decomposition for AI-led development - Ability to translate business requirements into agent workflows, tools, evaluation metrics, and deployable architectures - Hands-on exposure to Model Context Protocol (MCP) and AI orchestration layers connecting models, APIs, tools, and enterprise systems - Proficiency in developing LLM-based RAG (Retrieval Augmented Generation) - Strong debugging and problem-solving skills across data, model, prompt, and orchestration layers - Ability to communicate complex AI concepts through live demos, prototypes, and walkthroughs with both technical and non-technical stakeholders - Demonstrated ability to independently design and build working AI prototypes and demos (Note: The additional details of the company were not explicitly mentioned in the provided job description.) You will be responsible for owning the design and implementation of scalable, multi-step reasoning and agent-based workflows using the firms AI framework to build platform services, pipelines, and developer tooling. You will collaborate with the central AI team to translate framework releases into stable platform capabilities, working across platform teams and third-party vendors to deliver production-grade solutions. Your role will involve designing workflows that incorporate retrieval-augmented generation (RAG) across structured and unstructured data, implementing guardrails, validation layers, and hallucination-mitigation techniques aligned with the standards defined in the firm. You will translate business problems into impactful solutions incorporating automation across tools and workflows. Additionally, you will serve as the primary code-level reviewer for the AI systems and frameworks and define and enforce technology roadmaps, best practices, strategies, and standards for AI adoption across the organization. Your contribution will also be crucial in commoditizing AI by incorporating it into existing systems (front-end and back-end apps) and ensuring solution quality across performance, scalability, security, cost efficiency, and responsible AI considerations. Moreover, you will mentor and coach junior engineers on advanced AI techniques, best practices, and design. Key Responsibilities: - Own the design and implementation of scalable, multi-step reasoning and agent-based workflows - Collaborate with the central AI team to translate framework releases into stable platform capabilities - Design workflows incorporatin
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