• Design, develop and evolve agents and workflows using MCP-based architectures • Build RAG pipelines and context-retrieval mechanisms using vector databases • Integrate agents with APIs, tools and external services to execute complex flows • Develop agents in Python using Google ADK • Build and maintain agentic flows with LangChain and LangGraph • Integrate AI models and services via Vertex AI and Gemini models • Implement build, test and deployment pipelines for agents and workflows • Define architectural standards, reusable components and technical governance guidelines for the platform • Ensure solution observability through logs, metrics and tracing • Collaborate with technical teams to ensure consistent integration between AI agents and enterprise applications • Design solutions aligned with business processes, integrations and objectives • Ensure developed components are scalable, reusable and prepared for continuous evolution

• You'll design and maintain the infrastructure that powers client deliverables - ingestion pipelines, data models, transformation layers, and the orchestration that keeps it all running. • You'll build and ship AI applications - not prototype them. That means writing production-grade code, designing agent workflows, and integrating LLMs into systems where accuracy and reliability actually matter. • You'll architect agent systems with clear evaluation criteria, human-in-the-loop checkpoints where they matter, and monitoring that tells you when something goes wrong. • You'll own deployment end-to-end - containerized services, Kubernetes orchestration, cloud infrastructure, and the CI/CD pipelines that keep everything moving. • As a founding engineer, you'll help identify what we build repeatedly across engagements and turn it into durable internal infrastructure - shared data models, evaluation frameworks, deployment patterns.

Special Notice: This position is NOT contingent upon awarding of a project or needing a funding source. This is full-time employment with webAI. About the Role: We are seeking a Senior Forward Deployed AI Engineer to support our Public Sector initiatives focused on building and optimizing production ready AI systems for secure and distributed environments. This role sits at the intersection of machine learning, systems engineering, and deployment optimization, bridging research and real world implementation. You will be responsible for transforming prototype models into scalable, efficient, and reliable production systems that operate seamlessly across a spectrum of hardware from government cloud infrastructure to edge devices in restricted or disconnected environments. The ideal candidate will be based in Austin, Texas or in the Washington, D.C./Northern Virginia area. On a case-by-case basis, candidates who are fully remote. Qualified candidates who are not based in Austin, Texas may be asked to travel to our Austin, Texas headquarters. This role will require up to 25% travel, including occasional on-site work at customer locations to support deployment, troubleshooting, and integration of our platform within enterprise environments. Key Responsibilities: - Collaborate closely with customers to scope, deploy, and maintain AI solutions in production environments. - Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems. - Debug and optimize data pipelines and AI systems running on customer networks. - Translate complex, often ambiguous customer requirements into well-scoped technical solutions. - Work across the stack—from model inference on consumer hardware to infrastructure automation. - Read hardware schematics/logs to identify performance bottlenecks and suggest improvements. - Serve as a trusted technical advisor to enterprise clients, representing the engineering team externally. - Contribute feedback and insight to internal teams to continuously improve product robustness and usability. Required Skills & Qualifications: - 5+ years of combined experience in software engineering and machine learning. - Active US Security clearance - Proven track record of deploying and maintaining machine learning/AI systems in production. - Strong expertise in ML frameworks such as PyTorch, TensorFlow, ONNX, JAX, etc. - Experience debugging complex systems involving data pipelines, model inference, and hardware interaction. - Exceptional communication skills; able to challenge vague requirements and turn them into actionable plans. - Comfortable working in dynamic environments with high customer exposure. Preferred Qualifications: - Experience deploying models on edge devices or consumer hardware. - Familiarity with distributed systems, DevOps tooling, and performance tuning. - Prior experience in a customer-facing engineering role. - Proficiency in developing full stack applications - Knowledge of privacy-preserving AI and secure compute environments. - Master’s degree in a relevant technical discipline. We at webAI are committed to living out the core values we have put in place as the foundation on which we operate as a team. We seek individuals who exemplify the following: - Truth - Emphasizing transparency and honesty in every interaction and decision. - Ownership - Taking full responsibility for one’s actions and decisions, demonstrating commitment to the success of our clients. - Tenacity - Persisting in the face of challenges and setbacks, continually striving for excellence and improvement. - Humility - Maintaining a respectful and learning-oriented mindset, acknowledging the strengths and contributions of others. Benefits: - Competitive salary - Comprehensive health, dental, and vision benefits package - 401(k) match (U.S.-based employees only) - $200/month Health & Wellness stipend - Continuing Education support - $500/year Function Health subscription (U.S.-based employees only) - Free parking for in-office employees - Flexible Time Off (FTO) - Parental leave for eligible employees - Supplemental life insurance webAI is an Equal Opportunity Employer and does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of webAI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works.

• Architect and lead the development of agentic AI systems that automate and augment finance workflows. • Design and implement multi-agent systems leveraging LLMs, tool-use frameworks, and orchestration patterns. • Translate cutting-edge research in LLMs and agentic AI into scalable, production-ready solutions. • Establish guardrails, evaluation frameworks, and responsible AI practices to ensure safe, compliant, and reliable outputs. • Lead the design and implementation of advanced predictive models, including time series forecasting and attrition prediction across customer segments. • Develop interpretable, production-grade models that drive retention strategies and financial planning. • Define and standardize evaluation metrics, validation frameworks, and monitoring systems for model performance and drift detection. • Design and build scalable AI/ML systems with a strong emphasis on software engineering best practices. • Develop and integrate AI services into internal applications and workflows.