Hallmark - Healthcare Workforce Technology

Full-stack Engineer

• Lead teams and drive engineering best practices
• Design and develop scalable enterprise applications using C#, .NET Core/.NET 8+, ASP.NET Core, and Web APIs
• Develop modern, responsive front-end applications using Angular and TypeScript
• Build secure RESTful APIs and microservices
• Optimize application performance, scalability, and reliability
• Troubleshoot complex production issues and provide root cause analysis
• Manage Azure cloud infrastructure and services including AKS, Service Bus, and Application Insights
• Design and implement authentication and authorization using Microsoft Entra ID (Azure AD) and Azure AD B2C (Microsoft Entra External ID)
• Implement AI solutions
• Design, develop, and deploy enterprise-grade AI systems focused on reliability, scalability, monitoring, and measurable outcomes
• Lead or contribute to multiple AI initiatives while coordinating with engineering leads, product managers, architects, and offshore teams
• Independently drive proof-of-concepts, pilots, and production implementations
• Conduct technical design reviews and code reviews
• Mentor team members
• Report to Atul Jain

Senior Software Engineer

Customer Support

• Assist with technology-related questions from vendors and clients through email and virtual meetings
• Investigate, troubleshoot, and resolve support inquiries by gathering relevant information, identifying root causes, and determining appropriate next steps
• Manage day-to-day support activities, including tracking requests, following up on open items, and maintaining accurate documentation
• Communicate with leadership for vendor and client escalation as needed
• Assist with technology projects based on client request
• Attend training sessions and internal calls related to new features and product updates
• Understand functionality and translate learnings into effective client and vendor support
• Function in a fast-paced, customer service-oriented environment
• Use critical thinking to identify issues, assess options, and recommend effective actions
• Perform other duties as assigned based on business needs
• Own issues end-to-end with proactive communication to vendors, clients, and internal teams
• Resolve vendor and client questions efficiently with minimal escalation
• Maintain accurate, timely, and consistent documentation and follow-ups
• Ensure vendors and clients feel supported, informed, and confident using the technology

Support Specialist

AI Engineer

• Understand business problems and translate them into scalable AI/ML and Generative AI solutions
• Design, develop, and deploy enterprise-grade AI systems focused on reliability, scalability, monitoring, and measurable outcomes
• Lead or contribute to multiple AI initiatives while coordinating with engineering leads, product managers, architects, and offshore teams
• Independently drive proof-of-concepts, pilots, and production implementations
• Design and implement Agentic AI workflows for multi-step reasoning, orchestration, task automation, and intelligent decision support
• Build AI agents using LangChain, LangGraph, LlamaIndex, CrewAI, MCP, or equivalent platforms
• Implement memory management, evaluation pipelines, guardrails, failure recovery, and observability
• Develop prompt engineering strategies and optimize LLM interactions
• Build scalable RAG systems, including document ingestion, chunking, embeddings, vector databases, hybrid retrieval, re-ranking, and citation traceability
• Work with vector stores such as FAISS, Pinecone, and Weaviate
• Implement evaluation frameworks for retrieval quality and response accuracy
• Develop and optimize ML and deep learning models for predictive analytics, classification, forecasting, NLP, computer vision, and recommendation systems
• Participate in model fine-tuning, instruction tuning, RLHF, LoRA, and PEFT initiatives
• Build AI infrastructure on Azure, AWS, or GCP
• Implement MLOps practices including CI/CD, model monitoring, experiment tracking, infrastructure automation, and deployment orchestration
• Work with Docker, Kubernetes, Terraform, MLflow, Airflow, and GitHub Actions
• Optimize infrastructure usage, performance, and operational cost
• Collaborate with onsite and offshore engineering teams, technical leads, architects, QA, DevOps, and product stakeholders
• Mentor junior engineers and contribute to AI capability building

Software Engineer, AI/ML Focus

• Understand business problems and translate them into scalable AI/ML and Generative AI solutions
• Design, develop, and deploy enterprise-grade AI systems focused on reliability, scalability, monitoring, and measurable outcomes
• Lead or contribute to multiple AI initiatives while coordinating with engineering leads, product managers, architects, and offshore teams
• Independently drive proof-of-concepts, pilots, and production implementations
• Design and implement Agentic AI workflows for multi-step reasoning, orchestration, task automation, and intelligent decision support
• Build AI agents using LangChain, LangGraph, LlamaIndex, CrewAI, MCP, or equivalent orchestration platforms
• Implement memory management, evaluation pipelines, guardrails, failure recovery, and observability
• Develop prompt engineering strategies and optimize LLM interactions
• Build scalable RAG systems with document ingestion, chunking, embeddings, vector databases, hybrid retrieval, re-ranking, and citation traceability
• Work with vector stores such as FAISS, Pinecone, Weaviate, or similar technologies
• Implement evaluation frameworks for retrieval quality and response accuracy
• Develop and optimize ML and deep learning models for predictive analytics, classification, forecasting, NLP, computer vision, and recommendation systems
• Participate in model fine-tuning, instruction tuning, RLHF, LoRA, and PEFT initiatives
• Build scalable AI infrastructure on Azure, AWS, or GCP
• Implement MLOps practices including CI/CD, model monitoring, experiment tracking, infrastructure automation, and deployment orchestration
• Work with Docker, Kubernetes, Terraform, MLflow, Airflow, and GitHub Actions
• Optimize infrastructure usage, performance, and operational cost
• Collaborate with onsite and offshore engineering teams, technical leads, architects, QA, DevOps, and product stakeholders
• Mentor junior engineers and contribute to AI capability building

AI Software Engineer

Revenue Operations

• Lead forecasting, pipeline management, performance analytics, sales process optimization, CRM governance, and reporting
• Optimize and align the people, processes, systems, and data that drive revenue growth
• Partner with executive leadership to develop and execute the revenue operations strategy
• Align Sales, Marketing, Customer Success, and Finance processes to support revenue growth
• Develop scalable operating models and track revenue metrics, KPIs, and performance indicators
• Develop annual revenue plans, forecasts, targets, scenario models, and business plans
• Monitor pipeline health, conversion rates, bookings, revenue attainment, and forecast accuracy
• Build funnel instrumentation across lead sources from MQL through sales-accepted and sales-qualified stages
• Design account segmentation, scoring models, territory design, named-account coverage, and resource allocation
• Own lead scoring, routing, hand-off rules, and data hygiene standards
• Serve as business owner for CRM and revenue technology platforms, including HubSpot
• Establish CRM governance, data integrity requirements, process documentation, and system integrations
• Develop executive dashboards and reporting frameworks for sales, acquisition, retention, and revenue growth
• Administer sales compensation plans and quota setting; build capacity models and ramp plans
• Lead continuous improvement and standardize revenue lifecycle processes
• Build, lead, and develop a high-performing Revenue Operations team
• Establish performance expectations, coach team members, and manage external vendors and consultants as needed
• Report to Shachar Rabbe

Senior Software Engineer

Support Specialist

Software Engineer, AI/ML Focus

AI Software Engineer

Director of Revenue Operations