AI and ML architect for Commercial Content Supply Chain, focusing on the strategic design and implementation of advanced AI solutions to create a cutting-edge, AI-enabled content supply chain spanning from Medical Affairs through Commercial Marketing.
Compensation
The expected salary range for this position, based on the primary location of Warsaw Grafit is 170,100.00 PLN - 315,900.00 PLN. Final compensation will be determined by a number of factors, including your skills, experience, qualifications, and location. In addition to base pay, this role may be eligible for a discretionary annual bonus with a target of 15% subject to both individual and company performance.
Responsibilities
Designs solutions that meet product requirements, business priorities, and enterprise standards within a specific Solution Context.
Manages Non-Functional Requirements (NFR) and fitness functions.
Documents and evolves the architecture throughout the product life cycle and aligns with the architecture community for governance.
Design and refine multi-agent pipelines (using AWS building blocks, Bedrock AgentCore, and orchestration frameworks like LangGraph or Strands).
Work with data warehouse and analytics teams to turn complex models into high-performance, application-ready read interfaces and semantic caching layers.
Lead and support multiple cross-functional Forward Deployed Engineering project teams, ensuring efficient and effective execution while resolving issues as they arise, translating ambiguous, real-world problems into scalable AI/ML solutions.
AI and ML architect for Commercial Content Supply Chain focusing on the strategic design and implementation of advanced AI solutions to create a cutting-edge, AI-enabled content supply chain.
Compensation
Competitive salary based on the employment contract (Umowa o pracę). Annual bonus payment based on your performance.
Responsibilities
Design solutions that meet product requirements, business priorities, and enterprise standards within a specific Solution Context.
Manage Non-Functional Requirements (NFR) and fitness functions.
Document and evolve the architecture throughout the product life cycle and align with the architecture community for governance.
Design and refine multi-agent pipelines (using AWS building blocks, Bedrock AgentCore, and orchestration frameworks like LangGraph or Strands).
Partner with upstream data teams to turn complex models into high-performance, application-ready read interfaces and semantic caching layers.
Build and ship features for an AI-enabled revenue cycle management platform, including full-stack development, event-driven services, integrations, and AI agent orchestration.
Locations (2)
Chicago, Illinois, United States
United States
Compensation
The target base compensation for this position is $130,000 to $160,000 USD per year in most US locations. Final offer amounts are determined by multiple factors including location, local market variances, and candidate experience and expertise, and may vary from the amounts listed above.
Responsibilities
Build and ship features across a full-stack RCM worklist platform, from the user interface through backend services, APIs, and the data model
Develop event-driven services and workflows that route, prioritize, and track work across people and AI agents
Help build the shared automation foundation: the queues, state, and handoff logic that let an AI agent pick up a work item, finish it, or hand it back to a person, along with audit history, approval gates, and access controls for agent actions
Build and maintain integrations that connect the platform with EverHealth products, our clearinghouse, and third-party systems
Design, develop, and maintain scalable cloud-native applications and platform services on AWS, build and support large-scale data processing solutions using Apache Spark and AWS EMR, develop AI-powered applications using Generative AI technologies, RAG architectures, AI Agents, and AWS Bedrock services, create and maintain CI/CD pipelines, design and implement NoSQL database solutions, collaborate with cross-functional teams, perform code reviews, leverage GenAI tools, participate in Agile ceremonies, troubleshoot complex application, infrastructure, and data processing issues, contribute to architectural discussions and technology strategy initiatives.
Responsibilities
Design, develop, and maintain scalable cloud-native applications and platform services on AWS.
Build and support large-scale data processing solutions using Apache Spark and AWS EMR.
Develop AI-powered applications using Generative AI technologies, RAG architectures, AI Agents, and AWS Bedrock services.
Create and maintain CI/CD pipelines to enable reliable and automated software deployments.
Design, implement, and optimize NoSQL database solutions, preferably MongoDB Atlas.
Lead the technical direction of CI&T’s agent SDK platform, owning API design, versioning, and safety features while mentoring a team and driving multi‑agent orchestration.
Responsibilities
Own the SDK as a product: public API, semantic versioning, deprecation policy, migration guides and release hygiene
Design and evolve the adapter and host contracts for agent behavior across frameworks and deployment targets
Lead multi‑agent orchestration patterns and build runtime safety into the SDK
Define the extension model and support features
Own the parity and contract test suite for SDK and template releases
The base compensation range for the role in any of those locations is $136,000 USD - $253,000 USD. For any eligible US locations, unless otherwise noted, the base compensation range for this role is $118,400 USD - $219,800 USD. For Ontario, Canada, the base compensation range for this role is $140,600 CAD - $190,600 CAD.
Responsibilities
Lead and support multiple cross-functional Forward Deployed Engineering project teams
Architect and guide the design of scalable, secure AI/software solutions
Drive innovation by evaluating and adopting emerging AI methodologies
Manage and develop talent through hiring, performance management, coaching, and mentoring of engineers
Translate business needs into AI solutions by communicating and coordinating with project teams, partners, and stakeholders
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