A senior technical leadership role focused on designing and building production-grade Generative AI, RAG, and Agentic AI systems while working directly with stakeholders to deliver solutions.
Locations (2)
Hyderabad, Telangana, India
Bangalore, Karnataka, India
Responsibilities
Work directly with business and technical stakeholders to identify high-value AI use cases and convert ambiguous requirements into production-ready solutions.
Design and build Generative AI, Retrieval-Augmented Generation (RAG), Advanced RAG, and Agentic AI applications.
Build single-agent and multi-agent systems with planning, reasoning, tool calling, workflow orchestration, state management, memory, retries, exception handling, and human-in-the-loop approvals.
Develop and integrate Model Context Protocol (MCP) servers and clients to securely connect AI agents with enterprise tools, APIs, data sources, and workflows.
Develop and operate agentic AI products supporting Small Business Lending, focusing on LLM orchestration, evaluations, and production-ready AI systems.
Responsibilities
Design, build, and deploy machine learning and generative AI solutions to address business needs.
Build agentic AI systems with LLM orchestration frameworks such as LangChain, LangGraph, or similar tools.
Evaluate agent performance with golden and adversarial test sets, LLM-judge rubrics, and evaluation libraries.
Fine-tune SLMs and open-weight models for custom objectives.
Implement and tune safety guardrails, including input/output checks, prompt-injection defenses, PII handling, and spend limits; monitor effectiveness and false-positive impact.
Requirements
Bachelor’s degree
Master's degree
PhD degree in computer science or a data science-related discipline
An AI-Native Software Engineer focused on transforming the software development process into an AI-first model model using AI tools as a primary development partner while maintaining quality, security, and production readiness.
Locations (2)
Tampa, Florida, United States
United States
Responsibilities
Use AI-assisted development tools to generate, test, document, refactor, and improve software solutions.
Convert product and business requirements into clear technical prompts, implementation plans, and acceptance criteria.
Generate 80–90% of initial solution drafts using AI tools, then review, validate, and refine the output.
Detect and correct AI hallucinations, inaccurate assumptions, invalid code, security issues, and gaps in requirements.
Create automated tests to verify expected behavior and business outcomes.
Consultant Development Program (CDP) participant in Optum Advisory, focusing on AI/ML Engineering track, providing consulting and AI solution development for healthcare clients.
Locations (3)
Eden Prairie, Minnesota, United States
Nashville, Tennessee, United States
Washington, District of Columbia, United States
Responsibilities
Support strategic business transformation through technology, AI, process improvement, and innovation
Apply and integrate AI tools into client workflows, building and optimizing prompts
Participate in client-facing interactions and presentations
Support project delivery through requirements analysis, presentation development, meeting management, project planning, and budget support
Develop and support client-facing presentations and executive communication
Design, develop, and test AI-powered applications, from proof of concept to production-ready solutions, focusing on LLM-based solutions.
Compensation
A competitive compensation package, including a strong base salary and performance-based bonuses
Responsibilities
Design, develop, and test AI-powered applications, from proof of concept to production-ready solutions
Build and integrate LLM-based solutions, including use cases around RAG, document analysis, and text comparison, while connecting AI components to client systems and data sources
Develop back-end services, APIs, and user-facing interfaces or dashboards that make AI solutions accessible and usable by business teams
Design and run evaluation frameworks for AI outputs, including test sets, metrics, baselines, and traceability
Collaborate with business teams, data scientists, and engineers across client organizations and the Reply network
Lead the design, build, and delivery of cloud-native applications and services across consumer engagement and digital experience platforms, defining technical approaches and architecture for new capabilities, and owning services end-to-end.
Responsibilities
Lead the design, build, and delivery of cloud-native applications and services across consumer engagement and digital experience platforms
Define technical approaches and architecture for new capabilities, ensuring solutions are scalable, secure, resilient, and operationally efficient
Design the consumer data foundations powering personalization, activation, experimentation, and AI, including event platforms, analytics datasets, customer intelligence models, and transformation pipelines
Work with consumer and behavioral data to enable segmentation, personalization, activation, and real-time consumer experiences while maintaining appropriate privacy, consent, security controls and regulatory requirements
Take systems from prototype to production: recommendation engines, predictive models and intelligent automation used by real consumers at scale
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