Lead Applied AI Engineer/Scientist responsible for designing, developing, evaluating, and continuously improving applied AI systems to solve high-value construction and business problems.
Responsibilities
Define business problem and data readiness
Audit real-world inputs
Design data-labeling and validation approaches
Maintain traceability of outputs
Architect end-to-end AI agents and workflows
Requirements
Bachelor’s or advanced degree in computer science, machine learning, data science, engineering, or a related field
Support the development, testing, and documentation of AI-enabled applications using the Microsoft Azure stack.
Compensation
The hourly rate for this position is based on the level of education at the time the intern program begins: Sophomore $18.00 Junior $22.00 Senior (or May 2028 graduate) $22.00 Current graduate/law student $25.00
Responsibilities
Develop a focused AI solution using Python, REST APIs, Azure SDKs, Azure OpenAI, Azure MCP and Microsoft Foundry.
Assist with prompt engineering, structured outputs, tool calling, AI agents, and retrieval-augmented generation solutions.
Build or support integrations with Azure AI Search, Azure Storage, Azure SQL, Cosmos DB, and approved enterprise APIs.
Prepare and validate approved data for AI use cases, including document chunking, metadata creation, embeddings, and search indexing.
Create unit, integration, and AI evaluation tests covering accuracy, relevance, groundedness, safety, and edge cases.
Requirements
Enrollment in an associate’s, undergraduate or graduate program at a college or university is required. Recent graduates are not eligible for our Developmental Internship program.
Develop and deliver AI solutions, manage roadmap, pilot and production releases, evaluate datasets, provide user guidance and support multilingual operations.
Compensation
Competitive Salary: RM 4,000 - RM 5,000
Responsibilities
Develop AI delivery roadmap with use cases, data dependencies, business owners, baselines and acceptance criteria
Test pilots and production releases for agreed priority initiatives, supported by reusable integrations and documented operating procedures
Create evaluation datasets, monitoring dashboards and benefit reports showing quality, adoption, operating cost and operational impact
Provide user guidance, technical handover and a feedback loop that improves recommendations, knowledge and forecasts after deployment
Own customer-facing AI features end to end, from technical design and implementation through deployment, monitoring, and ongoing improvement.
Compensation
Base salary is $180,000 to $275,000 annually. Visa sponsorship is available.
Responsibilities
Own customer-facing AI features end to end, from technical design and implementation through deployment, monitoring, and ongoing improvement.
Build Python services and pipelines for retrieval, context construction, model and provider selection, structured extraction, orchestration, and monitoring.
Develop evaluations, representative datasets, benchmarks, regression tests, and launch gates to measure and improve AI quality.
Make AI systems resilient to latency, cost, provider errors, and unreliable intermediate outputs using retries, guardrails, verification, and fallbacks.
Improve retrieval and knowledge workflows, including embeddings, hybrid search, chunking, ranking, and reranking.
Full-stack AI role focused on building AI agents for healthcare patients, covering conversation design, prompts, tool calling, evals, and the APIs that make agents work in production.
Compensation
The typical salary range for this role is $160,000 to $210,000 USD, depending on skills, qualifications, and relevant experience.
Responsibilities
Design, build, and ship AI agents end to end, including conversation flows, prompts, tool and function calling, retrieval, memory, and the backend services agents depend on.
Build evaluation systems (offline test suites, simulated conversations, human review loops, and production monitoring) so we know an agent is good before and after it ships.
Improve instruction following, tool-calling reliability, latency, and cost across our LLM and speech stack.
Help design and build our next-generation voice agent platform, choosing the right models and architecture for each task based on quality, latency, and cost.
Partner with clinical, product, and customer teams to turn workflows like scheduling, refills, billing, and post-discharge check-ins into reliable agent behavior.
Lead the architecture and implementation of user-facing parts of Paystand’s systems, design and develop reusable libraries and frameworks, provide technical leadership and mentorship, and collaborate with product owners, designers, and other engineers to build the best user experience.
Responsibilities
Lead the architecture and implementation of user-facing parts of Paystand’s systems
Design and develop reusable libraries and frameworks that support complex web applications
Provide technical leadership and mentorship to other engineers
Collaborate with product owners, designers, and other engineers to build the best user experience
Ensure best practices in code quality, security, and performance
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