SOFTWARE ENGINEER

Duties:Client is seeking a Software Engineer to design and build back-end services that support our portfolio of data-centric clinical and analytic applications. These applications leverage cloud computing, big data, mobile, data science, data warehousing, machine learning using state of the art software development applications and frameworks. Our Software Engineers ensure that these cloud-based micro-services adhere to uptime and accuracy targets, are resilient, and scale as data volumes and traffic increase. They work closely with the data engineering, platform, and solutions teams to develop applications as required to benefit our practice and patients.Job Responsibilities:Works closely with the Product Owners, Product Managers, Architects to translate requirements into code. Developing services around data warehousing, big data, cloud computing, business intelligence, analytics and machine learning. Participate in DevOps, Agile, continuous development and integration frameworks. Programming in high-level languages such as Go, Python, Java etc. Work on deployment automation/configuration management with tools including but not limited to ADO, Puppet, Chef or Ansible or Azure Pipelines, CloudFormation, Terraform following a DevOps model. Ensure all appropriate documentation of processes and source code is created and maintained. Communicate effectively with peers, leaders, and customers throughout the organization. Participate in expert level troubleshooting and resolve problems through root cause analysis, data and system investigation. Continues to build knowledge of the organization, processes and customers. Performs a range of mainly straightforward assignments. Uses prescribed guidelines or policies to analyze and resolve problems. Receives a moderate level of guidance and direction. Design and implement MCP (Model/Agent Communication Platform) to enable agent-to-agent communication, orchestration, and observability. Build and scale data pipelines supporting AI/LLM and analytics use cases. Develop frameworks for agent control, monitoring, and traceability. Integrate MCP with enterprise data platforms, APIs, and AI services. Support data transformation, ingestion, and orchestration workflows. Ensure performance, scalability, and reliability of AI-driven data systems. Collaborate with engineering, data, and AI teams to deliver production-ready solutions. Required Skills:5 years of experience in software engineering or data engineeringStrong proficiency in:Python (required)APIs / microservices architectureExperience building:Data pipelines (ETL/ELT)Distributed systems or event-driven architecturesHands-on experience with:AI/LLM integration and workflowsAgent-based or orchestration frameworks (LangChain, Semantic Kernel, etc.)Strong understanding of:Observability (logging, tracing, monitoring)Data processing and transformation pipelinesData & Platform Expertise:Experience integrating AI systems with enterprise data platformsFamiliarity with:Streaming and batch processing frameworksCloud platforms (Azure, GCP, AWS)Understanding of scalable architecture patterns for AI and analyticsNice to Have:Experience with:MCP or similar agent communication frameworksLLMOps / MLOps practicesVector databases / embeddings / RAG architecturesCI/CD and DevOps pipelinesExposure to real-time observability toolsKey Competencies:Strong problem-solving and system design skillsAbility to work across AI, data, and platform engineering teamsSelf-driven with strong documentation and communication skillsExperience delivering production-grade AI systems