• Partner with Account Executives to support strategic sales opportunities. • Lead and participate in customer discovery sessions. • Gather, document, and validate business, clinical, operational, and technical requirements. • Develop solution strategies aligned with customer goals and platform capabilities. • Serve as a trusted advisor throughout the evaluation process. • Deliver compelling, tailored demonstrations to executive, clinical, operational, and technical audiences. • Build and maintain demonstration environments that reflect real-world customer scenarios. • Translate customer requirements into recommended solution approaches. • Support integration, interoperability, API, data exchange, and technical architecture discussions as needed. • Assist in completing responses to Requests for Proposal (RFPs), Requests for Information (RFIs), and security questionnaires. • Share market intelligence and customer feedback with Senior Director of Solutions Consulting.

• Provides presales solution architecture services across materially significant, strategically important clients and client groups. • Leads in the development of complex, tailored solutions, ensuring alignment with client needs and Unisys offerings, often incorporating emerging technologies. • Develops and delivers high-level presentations and demos, articulating the value of proposed solutions to senior-level managers and decision-makers. • Works with sales, product development and engineering teams to align proposed solutions with business objectives, ensuring technical feasibility and optimal client outcomes. • Oversees and contributes to preparation of technical responses for RFPs and RFIs, ensuring competitive and technically sound submissions. • Evaluates potential risks, ensuring that solutions comply with operational standards, security protocols and applicable regulations. • Fosters long-term client relations, providing trusted advice and counsel from a technical and operational perspective.

• Build and ship AI agents, APIs, and applications on Affirm's internal platform (Snowpark Container Services / Quicksilver). You own the full lifecycle: architecture, containerization, networking, secrets, CI/CD, monitoring, and fixing what breaks. • Turn messy business requirements from People Operations stakeholders into production systems. Integrate with Workday, Notion, and case management tools so AI surfaces real answers from governed content, not model guesses. • Navigate Affirm's existing security and data governance infrastructure to get AI systems running safely on people data. RBACs, data classification, and access policies already exist, but connecting them across systems (Workday, Snowflake, case tools) is where it gets messy. You figure out what's allowed, build within those constraints, and make sure employee data stays where it's supposed to. • Design reliability infrastructure for multi-model LLM services. Structured output validation, fallback chains, circuit breakers for external APIs, and quality controls that catch hallucination before users see it. • Work directly with non-technical stakeholders to scope problems, make architecture decisions, and give honest assessments of what AI can and can't do. You translate in both directions. • Contribute to the team's shared Python codebase, dbt models, and Snowflake infrastructure as part of a small, full-stack team that ships fast. • Own what you build. When something breaks in production, you diagnose and fix it.

• Design, develop, and maintain secure, scalable serverless integration solutions using AWS services. • Build and support cloud-native integrations between enterprise SaaS platforms, third-party vendors, and internal business systems. • Develop and secure REST APIs using AWS API Gateway and industry-standard authentication protocols. • Implement solutions using AWS services including Lambda, Step Functions, EventBridge, DynamoDB, S3, and AWS CDK. • Ensure solutions follow AWS security best practices, including IAM, KMS, Secrets Manager, CloudTrail, OAuth 2.0, OpenID Connect, and SAML. • Troubleshoot complex production issues, perform root cause analysis, and implement long-term solutions. • Write clean, maintainable, well-tested code following SDLC best practices and Kanban workflows. • Collaborate with Product Managers, Software Engineers, Architects, vendors, and business stakeholders to deliver high-quality integration solutions. • Mentor junior developers by providing technical guidance, code reviews, and development best practices. • Participate in architecture discussions and recommend improvements to system design, performance, security, and scalability. • Continuously evaluate and adopt modern AWS services, development tools, and AI-assisted technologies to improve engineering productivity. • Communicate project progress, technical risks, and key milestones to internal teams and leadership.