Forward Deployed Engineer

Please find below the JD:
Key Responsibilities
Define scalable, secure, resilient enterprise application architectures.
Design microservices, APIs, event-driven systems, distributed applications, and cloud-native platforms.
Assess applications and recommend modernization, re-platforming, and cloud-transformation strategies.
Create architecture blueprints, solution designs, technical roadmaps, and decision records.
Develop and troubleshoot full-stack solutions using Java and/or Python with React and/or Angular.
Build Spring Boot services, REST APIs, integrations, and production-grade proof-of-concepts.
Architect AWS solutions using services such as EKS, Lambda, S3, RDS, DynamoDB, API Gateway, EventBridge, SQS, SNS, CloudWatch, and Bedrock.
Build LLM applications, RAG solutions, AI Agents, Agentic workflows, and tool-enabled automation.
Apply AI-native engineering practices across requirements, development, testing, code review, documentation, and CI/CD.
Lead client workshops and clearly communicate architecture decisions, risks, and trade-offs.
Translate Life Sciences and Healthcare requirements into secure, compliant technology solutions.
Mentor engineering teams and promote architecture and development best practices.
Client and Domain Leadership
Work directly with client stakeholders to understand strategic priorities, technology challenges, and business requirements.
Facilitate architecture workshops, technical discovery sessions, design reviews, and solution demonstrations.
Translate Life Sciences and Healthcare requirements into practical enterprise technology solutions.
Advise clients on application modernization, cloud transformation, platform engineering, and AI adoption.
Communicate complex technical concepts clearly to business leaders, architects, engineering teams, and delivery stakeholders.
Support solution shaping, technical estimations, delivery planning, risk management, and executive-level technical presentations.
Provide technical leadership across Life Sciences and Healthcare areas such as Clinical and R&D, Commercial and Sales, Supply Chain, Manufacturing, Patient and Healthcare Platforms, Regulatory and Compliance, Data and Analytics, and Quality.
Mandatory Skills Required
Architecture and Technical Leadership
15–20 years of relevant technology experience.
Strong enterprise application and solution architecture experience.
Proven ability to architect complex, large-scale, secure, resilient, and highly available platforms.
Deep understanding of microservices, REST APIs, event-driven architecture, distributed systems, and cloud-native application patterns.
Experience creating architecture blueprints, technical roadmaps, solution designs, and Architecture Decision Records.
Strong application modernization, re-platforming, and re-architecture experience.
Ability to operate effectively in a client-facing architecture and engineering role.
Full-Stack Engineering
Strong hands-on development experience in Java and/or Python.
Hands-on experience with Spring Boot, REST APIs, microservices, and distributed applications.
Strong understanding of API design, authentication, authorization, databases, and integration patterns.
Hands-on frontend development experience with React and/or Angular.
Ability to work across frontend and backend layers and troubleshoot end-to-end application issues.
Demonstrated ability to contribute directly to code, prototypes, proofs of concept, and production solutions.
AWS Cloud Architecture
Strong hands-on experience with AWS architecture and cloud-native application development.
Practical experience with relevant AWS services, including: EC2, EKS, Lambda, S3, RDS, DynamoDB, VPC, IAM, CloudWatch, API Gateway, EventBridge, SQS and SNS
Amazon Bedrock and related AI/ML services
Experience with cloud migration, application modernization, and cloud optimization.
Strong understanding of cloud networking, security, scalability, resiliency, high availability, and observability.
Generative AI and Agentic Engineering
Strong practical experience implementing Generative AI and Agentic AI solutions.
Hands-on experience designing and developing AI agents and agentic workflows for enterprise use cases.
Experience with LLM-based applications, RAG, tool and function calling, orchestration, and AI-enabled automation.
Experience with MCP, LangChain, LangGraph, Amazon Bedrock, or similar technologies.
Experience delivering AI-enabled applications from proof of concept through production deployment.
Understanding of AI governance, security, observability, evaluation, and responsible AI practices.
Ability to identify and implement AI-driven automation opportunities across engineering and business processes.
Harness Engineering and AI-Native Delivery
Hands-on experience with Harness Engineering or comparable AI-native software engineering approaches.
Experience using AI engineering agents across requirements, architecture, development, testing, code review, documentation, and CI/CD.
Ability to establish AI-assisted and agentic SDLC practices across engineering teams.
Life Sciences and Healthcare
Strong Life Sciences and/or Healthcare domain experience.
Experience working with pharmaceutical, biotechnology, medical device, healthcare, or related organizations.
Ability to translate domain and business requirements into enterprise technology solutions.
Experience in one or more of the following areas: Clinical and R&D, Commercial and Sales, Supply Chain, Pharma or Clinical Manufacturing, Patient and Healthcare Platforms, Regulatory and Compliance, Data and Analytics or Quality
Nice to Have Skills
Exposure to Azure and/or Google Cloud Platform.
Experience with Claude Code, Cursor, GitHub Copilot, Devin, or equivalent AI coding and engineering tools.
Broader experience with AI/ML platforms and agent-orchestration technologies beyond Amazon Bedrock, LangChain, and LangGraph.
Experience introducing AI-assisted engineering practices across multiple teams or enterprise delivery programs.
Experience defining reusable accelerators, reference architectures, engineering guardrails, or governance models for AI-native software delivery

Work arrangement
Hybrid