Manager - Senior AI/ML Engineer
Summary
Leads end-to-end design and deployment of production-grade AI/ML and GenAI solutions, focusing on RAG platforms, agentic systems, and secure enterprise integrations using Python, AWS/Azure, and MLOps practices.
Role Overview
We are seeking a Senior AI/ML Engineer with 5–9 years of experience designing, building, and operating production-grade AI and Generative AI solutions. You will provide hands-on technical leadership across solution architecture, data and model pipelines, agentic systems, evaluation, cloud deployment, and observability. The ideal candidate pairs deep AI/ML expertise with strong software-engineering discipline and sound architectural judgment, and can lead delivery for complex enterprise use cases.
What You Will Do
Own AI/ML and GenAI solutions end to end — data pipelines, model and prompt workflows, APIs, evaluation, deployment, observability, and continuous optimization.
Design enterprise RAG platforms: secure ingestion, chunking, embeddings, hybrid/vector search, reranking, citations, and access-aware retrieval.
Build production agentic systems using tool/function calling, structured outputs, planning and memory, multi-agent orchestration, human-in-the-loop approvals, failure recovery, and auditable traces.
Architect and operate MCP clients and servers that expose enterprise tools, resources, and prompts — with secure transports (stdio, Streamable HTTP), authentication, least-privilege access, tenant isolation, and protection against prompt injection and unsafe tool execution.
Integrate agents with enterprise systems (document repositories, source control, ticketing, databases, ERP/CRM, cloud services) through reusable connectors and governance patterns.
Define evaluation strategies and quality gates for accuracy, groundedness, safety, latency, and cost, and establish end-to-end observability for agent and MCP activity.
Build production services in Python with strong engineering practices, GitHub-based CI/CD, and cloud-native deployment on AWS or Azure using Docker, Kubernetes, and infrastructure as code.
Partner with product, architecture, data science, security, and business stakeholders; lead design and architecture reviews and mentor engineers.
Required Qualifications
Bachelor's or Master's in Computer Science, Data Science, AI/ML, Engineering, or a related field — or equivalent practical experience.
5–9 years developing production software, data, ML, or AI solutions, including hands-on delivery of GenAI/LLM applications.
Advanced Python and practical experience with data/ML libraries (pandas, NumPy, scikit-learn, PyTorch, TensorFlow, or equivalent).
Strong grasp of LLM and agentic architecture: prompting, context engineering, embeddings, RAG, tool/function calling, structured outputs, orchestration, evaluation, and human-in-the-loop controls.
Proven experience designing APIs, distributed services, and event-driven or asynchronous workflows with secure tool execution for AI agents.
Hands-on experience with Git/GitHub and CI/CD, including automated build, test, security-scan, and deployment workflows.
Strong experience with AWS or Azure and containerized deployment using Docker; Kubernetes and infrastructure-as-code experience expected.
A current, role-relevant AWS AI/ML certification or Microsoft Azure AI certification is mandatory.
Hands-on production experience with Model Context Protocol (MCP) is mandatory — consuming and developing MCP servers, integrating clients with agent frameworks, defining tools/resources/prompts, managing stdio or Streamable HTTP transports, and implementing security, approvals, testing, and tracing.
MLOps/LLMOps practices: experiment tracking, model and prompt versioning, tracing, evaluation, monitoring, and cost optimization.
Preferred Experience
GenAI or agent frameworks such as OpenAI Agents SDK, LangGraph/LangChain, Semantic Kernel, AutoGen, LlamaIndex, Amazon Bedrock Agents, or Azure AI Foundry Agent Service.
Enterprise search and vector technologies (pgvector, Pinecone, Weaviate, Milvus, Elasticsearch/OpenSearch, Azure AI Search, Amazon OpenSearch, or equivalent).
LLMOps/observability platforms (MLflow or comparable) for tracing, evaluation, prompt management, and governance.
Strong SQL and data modeling; experience with streaming, workflow orchestration, data lakes, or lakehouse platforms.
Leading AI solutions in enterprise domains such as finance, accounting, operations, document intelligence, analytics, or compliance.
Responsible AI, model risk management, data governance, privacy, and regulatory/client-compliance familiarity.
Mentoring engineers, defining technical standards, and contributing to reusable platforms or open-source work.
About Riveron:
At Riveron, we partner with clients—from global multinationals to high-growth private entities—to solve complex finance challenges, guided by our DELTA values: Drive, Excellence, Leadership, Teamwork, and Accountability. Our entrepreneurial culture thrives on collaboration, diverse perspectives, and delivering exceptional outcomes. We are committed to fostering growth, both for our clients and our people, through mentorship, integrity, and a client-centric approach. This inclusive environment offers flexibility, progressive benefits, and meaningful opportunities for impactful work that supports well-being in and out of the office.
Want to stay connected with Riveron? Join our Talent Community to learn more about our growing firm and be considered for future opportunities.
Check us out on social media:
LinkedIn Glassdoor Instagram Facebook
Riveron Consulting is an Equal Opportunity Employer and believes that we are stronger together through our diversity. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, disability status, protected veteran status, sexual orientation, gender identity or any other characteristic protected by law.
Full time roles are eligible for a full range of benefits including medical, dental, and vision insurance, 401(k) with company match, and PTO. A complete description of all available benefits can be found at Riveron's Benefits page at . Contract roles are not eligible for benefits.
Fraud Alert
Please beware of fraudulent schemes or impersonations when going through the job application process. A Riveron employee will never recruit via text or extend unsolicited employment offers. Additionally, a Riveron employee will never ask you to exchange money or purchase anything as part of the recruiting process.
Artificial intelligence (AI) tools are used to support the hiring process in screening, assessing, and/or selecting applicants for this position. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
As published by ashby
Resume, Legal First Name and Legal Last Name, Email Address, Current Location
- Pronouns choose one · optional
- Phone Number optional
- Current Company optional
- LinkedIn Profile
- What is you official notice period ? is it negotiable ? if yes upto how many days it is negotiable ?
- Are you currently serving notice period ? if yes what is Last Working Day ?
- What Is your Current CTC (you can write in Range if not comfirtable to share Exact)
- Expected CTC
- Preferred Name optional
- Can you provide proof you are legally authorized to work in the United States? yes / no
- Do you now, or will you in the future, need sponsorship from an employer in order to obtain, extend, transfer, or renew your authorization to work in the United States? yes / no
- How did you find Riveron? choose one
- If you were referred, please list who referred you. optional
- Have you previously applied for employment, been employed with a client of, and/or been involved in a business capacity with Riveron, Clermont Partners, Conway MacKenzie, Winter Harbor, GBI Consulting, Yantra, Eden Data, Effectus Group or Cuesta Partners? yes / no
- If you answered "yes" to the question above, please explain below. If "no", please proceed to the next question. optional
- Do you have any ongoing or expected future professional commitments that could present a conflict of interest should you join Riveron (for example: consulting, teaching, Board of Directors)? yes / no
- If you answered "yes" to the question above, please explain below. If "no", please proceed to the next question. optional
- Do you have a significant interest (greater than 0.1%) in any company? yes / no
- If you answered "yes" to the question above, please explain below. If "no", please proceed to the next question. optional
- Please provide your home mailing address. written answer
- Add a cover letter or anything else you want to share. written answer · optional
- I certify that the facts contained in this application and the other information provided by me to Riveron Consulting, LLC ("The Company") during the application and hiring process are true and complete to the best of my knowledge and understand that, if employed, false or misleading representations provided by me to the company will constitute grounds for dismissal. I also understand and agree that, if employed, I have an obligation to notify the company promptly of any change in such facts, that I have an obligation to disclose to the company all information deemed by the company to be relevant thereto, and that my failure to comply with such obligations will constitute grounds for dismissal. choose any