I design AI agents that don’t just answer questions — they take actions. Using planning, tool-use, memory, and workflow branching, I build agentic systems that can coordinate across APIs, databases, and enterprise tools to automate complex, multi-step processes. Clients benefit from systems that are more autonomous, reliable, and measurably reduce manual workload.

I build enterprise-grade RAG pipelines that make LLMs accurate, grounded, and domain-specific. From document parsing and chunking to retrieval optimization and latency reduction, I design RAG systems that scale on cloud storage (S3/Blob/GCS) and integrate seamlessly into backend applications. This helps clients deliver fact-aware AI systems suitable for production.

I architect semantic search and embedding pipelines that enable deep contextual understanding of enterprise data. Whether using vector DBs, KGs, hybrid retrieval, or cross-modal embeddings, I ensure information is discoverable, linkable, and optimized for fast retrieval. This empowers clients with richer search, better recommendations, and AI systems capable of reasoning over structured + unstructured data.

I design automated LLM workflows that connect prompts, tools, APIs, and business rules into orchestrated pipelines. These automations power summarization, reporting, analysis, email generation, data extraction, and more — all while maintaining guardrails and auditability. Clients see immediate process acceleration and operational consistency.

I help teams adapt models to their domain through fine-tuning, prompt engineering, tool integration, and systematic evaluation. From domain adaptation (LoRA/FT) to developing evaluators for accuracy, hallucination, and safety, I ensure your AI behaves reliably in real-world environments. This reduces deployment risk and improves long-term performance.

I advise teams on designing AI-first products — from system architecture to data flows, tooling choices, scalability patterns, and DevOps integration. With a blend of backend engineering and GenAI expertise, I provide a blueprint that reduces technical debt, speeds up development, and ensures your product is production-ready from day one.

I design modular, domain-aligned microservice architectures that are easy to maintain, scale, and extend. By applying clean boundaries, event-driven patterns, and robust communication strategies, I help clients reduce coupling, increase agility, and evolve their systems without disruptive rewrites.

I architect secure, high-quality APIs and distributed backend systems that serve as the foundation for modern applications. From REST to GraphQL to async event streams, I ensure APIs are efficient, well-documented, and optimized for high-throughput interactions. This gives clients resilient data exchange and predictable system behavior across services.

I containerize services and deploy them on orchestrated environments like Kubernetes, ensuring reliability and consistent performance at scale. I help clients improve deployment speed, achieve zero-downtime rollouts, and standardize environments across dev, staging, and production.

I build backend systems optimized for speed, concurrency, resource efficiency, and clean engineering practices. Whether using .NET, Python, or distributed caching strategies, I enable clients to handle large workloads with lower latency and predictable performance under pressure.

I design automated CI/CD pipelines with strong DevOps alignment, enabling rapid and stable delivery. From automated testing and build pipelines to container packaging and release workflows, I help teams ship features faster with fewer failures—while retaining auditability and control.

I build systems with observability-first principles—logging, metrics, tracing, alerting—and reliability-focused engineering practices. I help clients scale workloads, prevent bottlenecks, improve fault tolerance, and achieve consistent uptime. This ensures their backend systems remain resilient even under unpredictable or high-traffic conditions.

I bring deep hands-on experience with hospital systems—including HIS, LIS, RIS/PACS, EMR/EHR, billing, pharmacy, and diagnostics—across India, Bangladesh, Bahrain, and South Asia. This domain knowledge helps clients avoid costly architectural mistakes and adopt digital systems that fit real-world clinical workflows, regulatory requirements, and hospital operations.

I help hospitals and healthcare organizations redesign patient, clinical, and administrative workflows for digital-first efficiency. From OP/IP journeys to lab automation and radiology workflows, I ensure systems support decision-making, reduce delays, eliminate redundancies, and create seamless patient experiences.

I guide healthcare teams in applying AI responsibly—triage assistants, automated reporting, operational analytics, patient routing, forecasting, and intelligent task automation. My blend of AI engineering and healthcare domain experience ensures solutions are safe, compliant, and aligned with clinical realities—not just tech demos.

I help organizations adopt HL7, FHIR, DICOM, LOINC, ICD-10, SNOMED CT, and standardized health data models to ensure clean interoperability. I also advise on HIPAA, GDPR, NDHM/ABDM guidelines, role security, audit trails, and privacy-by-design practices—critical for compliant AI and digital health systems.

I design structured EHR models, encounter templates, and clinical documentation flows optimized for accuracy, coding, and decision support. I also architect telemedicine platforms, integrating scheduling, triage, video consults, e-prescriptions, and follow-up workflows into a cohesive system.

I support PhD scholars, supervisors, and research labs with domain-informed technical guidance in healthcare AI, clinical data systems, RAG for medical knowledge, predictive modelling, and digital health architecture. My experience bridges academic research with practical engineering and healthcare operational realities.