This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking an experienced Staff Engineer to architect, deliver, and scale advanced AI/ML systems that directly drive business value. This role is ideal for a technical leader who thrives at the intersection of machine learning, architecture, and cloud engineering. - Architect and implement complex AI/ML systems that align with business and product objectives within the AWS cloud. - Serve as a subject matter expert on application engineering systems integrating with AI/ML components. - Drive large scale AI/ML project execution and foster cross functional collaboration between data science, ML engineering, and product teams. - Define and champion best practices for engineering, including code quality, system reliability, and operational excellence. - Mentor ML engineers to elevate team capabilities and maintain technical excellence. Qualifications - Authorized to work in the United States and not require work authorization sponsorship by our company for this position now or in the future. - 7+ years of experience in cloud native engineering development, with at least 3 years in a senior or staff level technical role. - Demonstrated experience of shipping/delivering large scale ML engineering projects. - Proven expertise in architecting and scaling production grade AI/ML systems, including model serving, training pipelines, and observability. - Deep understanding of distributed systems, data pipelines, and cloud native architectures (e.g., AWS, Kubernetes, Terraform, CI/CD frameworks). - Strong proficiency in Python and familiarity with frameworks such as TensorFlow, PyTorch, or similar ML libraries. - Demonstrated ability to drive technical alignment and execution across multiple teams or departments. - Experience applying ethical AI principles, including fairness, transparency, and privacy compliance, to real world projects. - Strong communication and leadership skills for influencing and guiding technical teams. - Advanced degree in Computer Science, Engineering, or a related field preferred; equivalent experience considered. Requirements - Tech Stack: Python, AWS (SageMaker, ECS, Lambda, S3, Fargate, etc.), Terraform, CI/CD frameworks. Benefits - Competitive compensation ranging from $170,000 - $200,000 per year PLUS quarterly bonus. - Medical, dental, vision, 401k program, and more. - Paid time off, including seven (7) federal holidays plus two (2) flex holidays for DEI. - Joining a rapidly growing organization. Company Description Trajector is where purpose meets progress. We specialize in medical evidence services that become the compass our clients rely on while navigating the intricate terrain of disability benefits. Our calling is clear: to make a real difference, infuse passion, and enhance the quality of life for the disabled community. As part of our global community, you'll join a team of over 1,800 dedicated individuals, each contributing their unique talents to streamline the path to benefits.

• Collaborate with the Head of AI, product managers, and engineers • Engineer and deploy ML models into real-time systems • Build robust, low-latency ML pipelines using Python, C++, and SQL • Apply adversarial learning and behavior modeling • Design and implement workflows that enhance data quality • Monitor, evaluate, and optimize deployed models • Present results and trade-offs to stakeholders • Contribute to Blackwall’s AI engineering practices by mentoring peers

• Design and build the core architecture for an enterprise workflow automation platform • Make critical technical decisions about stack, architecture patterns, and implementation independently • Create robust APIs, integrations, and workflow engines adaptable to diverse enterprise needs • Deploy virtually or on-site into customer organizations across the US • Conduct discovery sessions to understand workflows and requirements • Rapidly prototype and build custom solutions tailored to each enterprise • Iteratively integrate AI capabilities to enhance automation and drive value • Act as the technical face of the company during customer engagements • Work autonomously with minimal oversight from CEO and leadership • Make architectural decisions and push back constructively when needed • Move fast, ship quickly, and iterate.

• Design and implement AI/LLM‑powered capabilities including agent workflows, tool‑use actions, retrieval‑based systems, and structured output pipelines. • Build integrations with major model providers (OpenAI, Azure OpenAI, Anthropic) and open‑source model ecosystems. • Develop and optimize RAG pipelines, embeddings, vector search, and semantic retrieval patterns. • Implement evaluation harnesses, guardrails, prompt management, and safety validation workflows. • Collaborate with backend, frontend, and data engineers to deliver scalable AI‑driven features. • Integrate AI capabilities into Kubernetes‑based microservices environments using modern APIs and deployment patterns. • Configure and operate model‑serving environments (vLLM, TGI, KServe) including tuning for latency, throughput, and cost. • Implement observability for AI systems including telemetry, metrics, traces, structured logs, and prompt evaluations. • Support CI/CD automation, model versioning, feature flagging, and safe rollout of AI functionality. • Contribute to documentation, architectural diagrams, and reusable internal AI patterns. • Mentor junior engineers and support skill development across AI engineering best practices.