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Key Responsibilities:
- Drive corporate sales by onboarding and managing corporate clients
- Handle RWA (Resident Welfare Association) sales and partnerships
- Develop and manage key accounts, ensuring long-term relationships
- Identify new business opportunities and close enterprise-level deals
- Coordinate with internal teams across Bangalore and other locations
- Achieve revenue targets through strategic planning and execution
- Conduct presentations, negotiations, and contract closures
- Maintain strong post-sales engagement, ensure account retention and generate revenue for our partner hospitals through corporate and RWA engagement.
Required Skills & Experience:
- Minimum 5+ years of experience in Corporate Sales / RWA Sales / B2B Sales
- Strong experience in Key Account Management
- Proven track record of closing high-value corporate deals
- Excellent communication, negotiation, and stakeholder management skills
- Ability to work independently and manage multiple accounts
- Prior experience in healthcare, insurance, fintech, or employee benefits will be an added advantage
Java
Spring BootJava Backend Developer (6–9 Years)
Mandatory Skills:
- Strong Core Java (Java 8/11/17)
- Spring Boot
- Microservices Architecture
- RESTful API Development
- Collections, Multithreading, Java 8 Streams
- SQL (Oracle/MySQL/PostgreSQL)
- JPA/Hibernate
- Git, Maven, Jenkins
- Unit Testing (JUnit/Mockito)
Good to Have:
- Kafka/Event-Driven Architecture
- Docker/Kubernetes
- Cloud (AWS/GCP/Azure)
Responsibilities:
- Design and develop scalable backend microservices.
- Build secure REST APIs for enterprise applications.
- Write clean, optimized, production-quality code.
- Debug production issues and perform code reviews.
- Work in Agile teams and contribute to CI/CD pipelines.
Experience: 6–9 Years
Location: Bangalore / Mumbai / Chennai (Hybrid)
grafanaPrimary Skills:
Observability - ELK (Elactic/Kibana), Prometheus, Grafana, PromQL
Software and automation - Java, Python/Shell/Bash, Rest-SOAP API, docker containerization, Kubernetes, Kafka
Reliability and DR engineering - Distributed architecture and distributed system fundamentals, micro services, and event-driven architecture.
Cross-team coordination, incident triage and resolution, leadership and stakeholder management.
Secondary Skills:
Lang-chain, Langraph, RAG, MCP
Experience with working on LLM's and integrating with the existing applications
Python - FastAPI
Cache - Redis
Program Details:
Design, build, and ship LLM-powered and agentic product features that enhance the team efforts and outcomes.
Build agentic AI systems that reason over context, invoke tools, take real actions, and recover gracefully from failure.
Work on integrating the existing AI tools and should know major AI frameworks and libraries.
Own service reliability and operational governance by defining SLA's, managing error budgets, and reporting reliability (MTTD, MTTR) to leadership for prioritization, risk decisions and planning.
Architect and continuously optimize the observability of platform using Kibana/Elastic (ELF) along with other observability tools like Prometheus, Grafana (dashboards, metrics, alert lifecycle), improving detection quality, reducing noise/toil, and enabling faster triage and measurable uptime improvements.
Engineer advance alerting and automation capabilities with Kibana alerting and anomaly detections and integrating response workflows (routing, runbooks, remediation scripts) to standardize on-call execution and accelerate restoration of services.
Lead incident response for customer-impacting issues across teams-coordination, communications, service restoration, and blameless RCA-then corrective actions that prevent recurrence and reduce operational risk.
Design, automate and validate Disaster Recovery and failover for critical services/journeys (RTO/RPO alignment, DR Drills), ensuring resiliency under failure scenarios and improving recovery.
Consult and partner with application teams by providing production readiness inputs (Resiliency patterns, availability, performance/capacity considerations) and driving platform enhancements that improve stability while optimizing infrastructure and observability spend.
If you are interested for this role, kindly acknowledge this email with your interest.
Requirements
- 12+ years of overall SAP consulting/architecture experience, with at least 4–5 years on SAP BTP and its predecessor (HCP/SCP).
- Minimum 3 full-cycle SAP BTP implementation projects as Solution/Integration Architect or Technical Lead in large enterprise environments.
- Hands-on delivery experience with SAP AI Core or at least 2 production AI/ML implementations in the SAP ecosystem (not just POC/demo).
- Deep familiarity with SAP S/4HANA cloud integration patterns, side-by-side extensibility, and ABAP-to-BTP migration strategies.
- Experience leading architecture design sessions, reviewing technical deliverables, and owning solution blueprints for enterprise clients.
- Exposure to multi-cloud environments and ability to design hybrid landscapes integrating SAP BTP with hyperscalers.
- Prior client-facing consulting or practice-building experience in a Big 4, SAP partner, or independent software vendor context preferred.
Roles & Responsibilities
- Contribute to IP creation — accelerators, reusable assets, reference architectures, and practice-building initiatives.
- Design BTP solution architectures covering SAP Integration Suite, Extension Suite, Data and Analytics cloud, and SAP Build portfolio.
- Architect and deploy SAP AI Core pipelines — model serving, ML Ops workflows, and custom inference endpoints in production.
- Lead development of cloud integration flows using SAP Integration Suite (CPI), API Management, and Event Mesh for hybrid and multi-cloud landscapes.
- Drive SAP BTP subaccount strategy, environment provisioning, identity and access management (IAS/IPS), and security posture.
- Define and govern integration patterns — synchronous/asynchronous, event-driven, point-to-point, and hub-and-spoke models.
- Enable AI use cases using SAP AI Launchpad, Foundation Models, and third-party LLM integrations via BTP Generative AI Hub.
- Build and mentor a team of consultants and developers; run architecture workshops, enablement sessions, and CoE activities.
- Evaluate and recommend SAP BTP service mix against custom cloud-native alternatives to optimize TCO and roadmap alignment.
- Stay current with SAP roadmap, RISE with SAP, GROW with SAP, and relevant cloud platform evolution (AWS, Azure, GCP).
Certifications
- Preferred / expected - C_BTP_2408 — SAP Certified Associate, BTP ; P_BTP_2408 — SAP Certified Professional, BTP ; C_AIG_2412 — SAP AI & GenAI ; C_ARCIG_2404 — SAP Integration Solution Architect ; C_HANADEV — SAP HANA Cloud Developer
- Good to have - AWS Solutions Architect, Azure / GCP Professional ; SAP Analytics Cloud
JavaSpring BootJava Backend Developer (6–10 Years)
Mandatory Skills:
- Core Java 8+ (Collections, Streams, Multithreading)
- Spring Boot
- Microservices Architecture
- RESTful API Development
- SQL (Oracle/MySQL/PostgreSQL)
- JPA/Hibernate
- Design Patterns & OOP
- Distributed Systems
- Kafka/RabbitMQ (Preferred)
- AWS/Azure (Preferred)
- CI/CD, Git, Jenkins, Docker/Kubernetes (Preferred)
Responsibilities:
- Design and develop scalable backend microservices.
- Build secure and high-performance REST APIs.
- Work on distributed systems and production-grade applications.
- Optimize application performance and troubleshoot production issues.
- Participate in code reviews and Agile development.
Preferred Background:
- Product engineering or enterprise backend development.
- Strong coding skills in Java with hands-on experience in live problem solving.
Experience: 6–10 Years
Location: Bangalore / Mumbai / Chennai (Hybrid)
grafanaPrimary Skills
- Observability: ELK (Elasticsearch/Kibana), Prometheus, Grafana, PromQL
- Automation: Java/Vert.x or Python (FastAPI), Shell/Bash, REST/SOAP APIs
- Cloud & Platform: Docker, Kubernetes, Kafka, Redis
- Reliability Engineering: Distributed Systems, Microservices, Event-Driven Architecture, DR & Incident Management
- Stakeholder Management & Cross-functional Collaboration
Secondary Skills
- Agentic AI: LangChain, LangGraph, RAG, MCP
- LLM Integration & AI Frameworks
- Python (FastAPI)
Key Responsibilities
- Build and deploy LLM-powered Agentic AI solutions with tool calling and autonomous workflows.
- Integrate AI capabilities into existing applications using modern AI frameworks.
- Own platform reliability through SLAs, SLOs, error budgets, MTTD/MTTR, and operational governance.
- Enhance observability using ELK, Prometheus, Grafana, and advanced alerting.
- Lead incident response, RCA, disaster recovery, and resiliency initiatives.
- Drive production readiness, automation, platform stability, and infrastructure optimization.
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