Senior AI Engineer

We are seeking a Senior AI Engineer to design, build, and scale enterprise-grade AI platforms leveraging frontier Large Language Models (LLMs). This role sits at the intersection of AI engineering, platform architecture, and applied GenAI, with a strong emphasis on productionization in regulated environments (financial services, wealth, capital markets). You will play a key role in operationalizing AI at scale, building reusable capabilities, and enabling secure, governed adoption of LLM-powered solutions across the enterprise., AI Platform Engineering · Design and build scalable AI platforms supporting LLMs, RAG pipelines, and multi-model orchestration · Develop reusable frameworks for prompt management, model routing, evaluation, and monitoring · Implement LLMOps / MLOps pipelines for continuous integration, deployment, and lifecycle management · Architect API-first AI services for enterprise-wide consumption. Frontier LLM Integration · Integrate and optimize models from providers like OpenAI, Anthropic, Google DeepMind, and open-source ecosystems · Build multi-model strategies (closed + open source) for performance, cost, and governance · Implement advanced techniques: · Retrieval-Augmented Generation (RAG) · Tool use / agents · Fine-tuning and embeddings · Context optimization and memory systems. Enterprise AI & Governance · Design systems aligned with security, compliance, and data privacy requirements · Implement guardrails, auditability, and explainability in AI workflows · Enable safe AI deployment in distributed environments (e.g., advisor desktops, hybrid cloud). Applied AI Solutions · Build AI-driven use cases such as: · Intelligent document processing (e.g., wealth plans, research docs) · Advisor copilots and decision support systems · Knowledge assistants and enterprise search · Partner with business teams to translate use cases into scalable AI solutions. Performance & Evaluation · Develop evaluation frameworks for accuracy, hallucination detection, and model performance · Optimize latency, throughput, and cost for production deployments · Establish benchmarking and observability standards, As a Senior DevOps Engineer, you will play a crucial role in shaping the future of AI systems by designing and maintaining scalable infrastructure solutions. Your expertise will di…

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· 7-12+ years in software engineering, with 3+ years in AI/ML engineering or GenAI · Strong proficiency in: · Python, APIs, microservices architecture · LLM frameworks (LangChain, LlamaIndex, etc.) · Hands-on experience with: · RAG pipelines, vector databases (Pinecone, FAISS, etc.) · Cloud platforms (AWS, Azure, GCP) · Deep understanding of transformer models, LLM architecture, prompt engineering, and context handling · Experience building production-grade AI systems (not just POCs). Preferred Qualifications · Experience in financial services / wealth / capital markets · Familiarity with regulated AI deployments (compliance, DLP, governance) · Exposure to agentic AI systems and autonomous workflows · Experience with fine-tuning / LoRA / model optimization · Knowledge of data engineering pipelines and real-time architectures.

• $45.00 per hour