About Alvarez & Marsal
Alvarez & Marsal (A&M) is a global consulting firm with entrepreneurial, action and results-oriented professionals. We take a hands-on approach to solving our clients' problems and assisting them in reaching their potential.
Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging work—guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity—are why our people love working at A&M.
For details, please visit the company website:
http://www.alvarezandmarsal.com
Our DTS team provides following services to clients:
Data & Applied Intelligence - Helping clients in harnessing the power of data and cutting-edge analytics to drive intelligent decision-making and transform businesses.
Product and Innovation - Empowering clients to innovate, develop, and launch products that drives growth and competitive advantage.
Technology M&A and Strategy - Assist clients to manage the technology aspects and business enablement of complex M&A, integrations and carve-outs.
Technology Transformation - A&M helps clients create a scalable, cost-effective IT function that delivers the company's strategic vision and priorities.
Lead the design, development, and deployment of Generative AI and LLM-based solutions to address complex business problems across functions such as CPG, Retail, and Supply Chain.
Architect and implement agentic AI workflows using modern frameworks, including multi-agent systems, tool calling, memory, planning, and human-in-the-loop controls.
Design and operationalize RAG-based pipelines using embeddings, vector databases, prompt orchestration, re-ranking, and guardrails to deliver accurate and context-aware AI solutions.
Develop and deploy machine learning and GenAI solutions on Azure, ensuring scalability, reliability, security, and production readiness.
Establish and manage LLMOps practices, including model lifecycle management, prompt/version control, CI/CD pipelines, experimentation, deployment, and monitoring.
Implement observability, telemetry, and tracing for GenAI systems, including latency tracking, token usage monitoring, prompt-response logging, failure analysis, and user feedback capture.
Define and maintain evaluation frameworks for LLM and agentic systems, measuring groundedness, relevance, accuracy, safety, task completion, and cost-performance tradeoffs.
Use Python for data preprocessing, model development, experimentation, orchestration, and integration of AI workflows.
Build and integrate REST APIs using Flask/FastAPI to enable seamless access to models and GenAI services across enterprise applications.
Containerize models and applications using Docker to streamline deployment, portability, and environment consistency.
Collaborate with cross-functional stakeholders including business, product, engineering, data, and cloud teams to identify use cases and deliver custom AI solutions.
Drive production optimization of GenAI systems for accuracy, inference speed, cost efficiency, scalability, and real-time performance.
Ensure adherence to responsible AI, governance, security, privacy, and compliance standards for enterprise AI implementations.
Mentor and guide team members on best practices in GenAI architecture, prompt engineering, agent design, LLM evaluation, and production deployment.
Stay current with the latest advancements in Generative AI, foundation models, agentic frameworks, cloud technologies, and enterprise AI platforms
6 - 11 years of experience in data science, machine learning, or AI, with strong recent experience in LLMs, Generative AI, and production AI systems.
Proven experience designing and delivering AI/ML solutions across industries such as CPG, Retail, and Supply Chain.
Hands-on experience with LLMs, prompt engineering, RAG architectures, vector databases, embeddings, and re-ranking techniques.
Strong experience with agentic AI frameworks such as LangChain, LangGraph, MAF, Semantic Kernel, CrewAI, or similar orchestration platforms.
Experience deploying and managing AI/ML solutions on Azure, including cloud-native services, monitoring, and scalable infrastructure.
Strong programming skills in Python for model development, orchestration, APIs, and experimentation.
Experience building APIs and AI services using Flask/FastAPI and deploying containerized solutions using Docker.
Familiarity with LLMOps, observability, telemetry, tracing, and monitoring for production GenAI applications.
Experience defining and implementing evaluation frameworks for LLM applications, including automated and human-in-the-loop assessment approaches.
Strong understanding of responsible AI, governance, model risk, privacy, and enterprise security requirements.
Ability to optimize GenAI solutions for accuracy, latency, scale, and cost efficiency in production environments.
Proven ability to work with cross-functional teams and translate business needs into scalable AI solutions.
Strong communication, stakeholder management, and team leadership skills.
We recognize that our people are the driving force behind our success, which is why we prioritize an employee experience that fosters each person’s unique professional and personal development.
Our robust performance development process promotes continuous learning, rewards your contributions, and fosters a culture of meritocracy. With top-notch training and on-the-job learning opportunities, you can acquire new skills and advance your career.
We prioritize your well-being, providing benefits and resources to support you on your personal journey.
Our people consistently highlight the growth opportunities, our unique, entrepreneurial culture, and the fun we have together as their favorite aspects of working at A&M.
The possibilities are endless for high-performing and passionate profession
At A&M, we know our people drive our growth, and we're focused on providing an employee experience that supports professional and personal development.
We provide our team with a robust performance development process which encourages continuous learning and development that rewards you for your contributions.
We have the best technical and formalized on-the-job training and offer endless opportunities for professionals to acquire new skills.
We also prioritize your well-being and provide personal tools and resources to support you through your personal journey.
At Alvarez & Marsal, our core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity guide everything we do, shaping a culture rooted in entrepreneurship, impact, and integrity. We trust our people to take ownership early, contribute to meaningful challenges, and drive results that matter. We empower growth and champion diverse perspectives. Above all, we value doing the right thing. For those ready to roll up their sleeves, lead with integrity, and be difference makers, this is where it starts.
It is Alvarez & Marsal’s practice to provide and promote equal opportunity in employment, compensation, and other terms and conditions of employment without discrimination because of race, color, creed, religion, national origin, ancestry, citizenship status, sex or gender, gender identity or gender expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, family medical history, genetic information or other protected medical condition, political affiliation, or any other characteristic protected by and in accordance with applicable laws. Employees and Applicants can find A&M policy statements and additional information by region here.
Please note that as per A&M policy, we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that A&M will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.
