Note: The job is a remote job and is open to candidates in USA. MathCo is an AI and analytics consultancy that helps global enterprises turn data, analytics, and AI into measurable business outcomes. The Senior Forward Deployed Engineer (AI) partners with clients to frame ambiguous business challenges, architect scalable solutions, build production-ready AI and software systems, and lead deployment, adoption, and handoff. The role serves as the primary technical owner while coordinating business strategy, AI, data, cloud, software engineering, and stakeholder management.
Responsibilities
- Collaborate closely with client stakeholders to understand business objectives, workflows, and decision-making processes
- Identify opportunities where AI, analytics, and data-driven solutions can create measurable impact
- Separate assumptions from facts and establish a clear understanding of the problem before solution design begins
- Define success metrics and align stakeholders on expected outcomes
- Design scalable, secure, and production-ready architectures aligned with client technology ecosystems
- Evaluate technical trade-offs and guide architectural decisions across cloud, data, AI, and application layers
- Ensure solution designs account for security, governance, integration, scalability, and operational requirements
- Document architectural decisions and implementation approaches clearly
- Develop and deploy production-grade AI, analytics, and software solutions using real-world client data
- Build reusable, maintainable, and scalable code across the solution stack
- Implement GenAI-enabled capabilities, including retrieval-augmented generation (RAG), agentic workflows, evaluation frameworks, and orchestration mechanisms
- Validate solution effectiveness through structured testing and measurable performance outcomes
- Lead discovery workshops, solution reviews, working sessions, and executive presentations
- Communicate technical concepts effectively to both business and technical audiences
- Proactively identify risks and trade-offs while providing actionable recommendations
- Manage scope, priorities, timelines, and stakeholder expectations throughout the engagement
- Create comprehensive transition packages, including:
- Solution architecture documentation
- Operational runbooks
- Validation and testing evidence
- Deployment guidelines
- Knowledge transfer materials
- Ensure successful adoption by client teams and support transition to production ownership
- Continue providing architectural guidance during scaling and implementation
- Leverage AI tools, accelerators, and digital agents to improve solution delivery and engineering productivity
- Build reusable assets, playbooks, and frameworks that can be applied across engagements
- Mentor and guide delivery team members through structured documentation and knowledge-sharing practices
Skills
- • 10–15 years of experience designing, building, and deploying software, data, analytics, or AI solutions
- • Demonstrated ownership of production systems and business-critical deliverables
- • Experience operating in client-facing or highly collaborative environments
- • AI/ML Engineering
- • Data Engineering
- • Backend Engineering
- Working knowledge across adjacent domains, including cloud architecture, data platforms, APIs, and front-end technologies
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Agentic AI workflows
- Prompt and context engineering
- AI evaluation and monitoring frameworks
- Responsible AI implementation practices
- Microsoft Azure
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Databricks
- Ability to work within complex enterprise environments that include legacy systems, modern platforms, and third-party applications
- • Proven experience navigating ambiguity and defining structured solutions
- • Strong stakeholder management and requirements-gathering skills
- • Ability to translate business problems into scalable technical solutions
- • Demonstrated ability to make informed decisions under uncertainty
- • Exceptional verbal and written communication skills
- • Experience presenting recommendations and technical decisions to senior stakeholders and business leaders
- • Ability to influence cross-functional teams without direct authority
- • Enthusiasm for using AI tools and digital assistants to improve productivity and outcomes
- • Strong learning agility and curiosity about emerging technologies
- • Ability to operate independently in distributed, remote-first environments
- • Experience in consulting, solutions engineering, customer engineering, or forward deployed engineering roles
- • Experience delivering AI transformation initiatives at enterprise scale
- • Consumer Packaged Goods (CPG)
- • Retail
- • Life Sciences & Pharmaceuticals
- • Manufacturing
- • Financial Services
- • Experience delivering fixed-scope, outcome-based, or value-based engagements
- • Experience leading distributed teams and managing project execution through architecture documents, ADRs, runbooks, and implementation playbooks
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