AI & Emerging Technology Innovation
•Define and drive the AI/innovation roadmap aligned to business strategy and measurable outcomes.
•Identify, evaluate, and prototype emerging technologies (Generative AI, LLMs, ML, agentic workflows, RAG) and convert successful proof-of-concepts into production solutions.
•Design and implement AI-powered features such as intelligent assistants, document/data extraction, recommendation systems, forecasting, and anomaly detection.
•Establish frameworks for LLM integration, prompt engineering, RAG pipelines, vector search, fine-tuning, and model evaluation .
•Implement Responsible AI practices—governance, bias mitigation, data privacy, guardrails, and cost/performance optimization.
•Run innovation sprints, hackathons, and tech-scouting to build a culture of experimentation.
Cloud Solution Architecture (AWS)
•Architect scalable, secure, and cost-optimized solutions on AWS.
•Design and build using core AWS services: - Compute: Lambda, ECS/EKS, EC2
•AI/ML: Bedrock, SageMaker, Comprehend, Textract, Kendra
•Data & Storage: S3, RDS, DynamoDB, Redshift, Aurora
•Integration: API Gateway, Step Functions, EventBridge, SQS/SNS
•Observability & Security: CloudWatch, IAM, KMS, Secrets Manager
•Implement Infrastructure as Code (Terraform / AWS CDK / CloudFormation) for repeatable, automated deployments.
•Build ephemeral and self-service environments to accelerate prototyping and experimentation.
•Optimize cloud utilization, performance, and cost.
Data & Database Engineering
•Design and optimize relational and NoSQL databases (SQL Server, PostgreSQL, MySQL, Oracle, DynamoDB, MongoDB).
•Architect data pipelines, ETL/ELT flows, and data models supporting analytics and AI workloads.
•Implement vector databases (pgvector, OpenSearch, Pinecone) to support semantic search and RAG.
•Ensure data quality, governance, lineage, security, and compliance.
•Enable data-driven decision-making through dashboards, analytics, and reporting.
Application Engineering (.NET / Java)
•Lead the design and development of enterprise-grade applications and microservices using .NET (C#) and/or Java (Spring Boot) .
•Define architecture standards, coding best practices, API design (REST/GraphQL/gRPC), and design patterns.
•Build robust, secure, high-performance backend services and integration layers.
•Modernize legacy applications and migrate workloads to cloud-native architectures.
Automation & Engineering Excellence
•Embed intelligent automation across the full software delivery lifecycle.
•Design and build automated frameworks for: - CI/CD and deployment automation
•Testing (UI, API, end-to-end) using Playwright
•Infrastructure provisioning and teardown
•Data generation and environment setup
•Create configurable mock services, simulators, and stubs for third-party dependencies to enable independent development and testing (success/failure scenarios, timeouts, latency, rate limiting, auth failures, edge cases).
•Integrate automation and quality gates into CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins).
•Enable parallel execution, self-service capabilities, and reusable platforms for engineering teams.
DevOps & Observability
•Champion DevOps culture—containerization ( Docker/Kubernetes ), automation, and continuous delivery.
•Implement monitoring, logging, tracing, and diagnostics for applications and infrastructure.
•Drive reliability, scalability, security, and execution speed across platforms.
Leadership & Collaboration
•Mentor and technically lead cross-functional engineering teams.
•Partner with product, business, and leadership stakeholders to align innovation with strategic goals.
•Communicate complex technical concepts to technical and non-technical audiences.
•Evangelize best practices, reusable assets, and a culture of continuous learning.
Required Skills
AI & Machine Learning
•Hands-on experience with Generative AI / LLMs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI).
•Experience with RAG, prompt engineering, embeddings, vector databases, and model evaluation .
•Familiarity with ML frameworks and MLOps concepts.
•Understanding of Responsible AI, governance, and security.
Programming & Application Development
•Strong hands-on expertise in .NET (C#) and/or Java (Spring Boot) .
•Experience designing microservices, APIs, and distributed systems.
•Working knowledge of Python and TypeScript/JavaScript is a strong plus.
AWS & Cloud Infrastructure
•IAM, Lambda, ECS/EKS, API Gateway, S3, DynamoDB, RDS/Aurora, Step Functions, EventBridge, CloudWatch.
•AI/ML services: Bedrock, SageMaker, Textract, Comprehend.
•Infrastructure as Code : Terraform (preferred), AWS CDK, CloudFormation.
Databases & Data
•Strong SQL and NoSQL database design and optimization.
•Data modeling, ETL/ELT pipelines, and data governance.
•Vector/semantic search technologies.
Automation & DevOps
•Playwright for UI, API, and end-to-end automation; cross-browser testing (Chrome, Edge, Firefox).
•Service virtualization & mocking: WireMock, MockServer, Hoverfly, Mountebank, Pact .
•Containerization: Docker, Kubernetes .
•CI/CD: GitHub Actions, Azure DevOps, Jenkins .
•Test data generation and management
Ideal Candidate Profile
•12+ years of experience in software engineering, solution architecture, platform engineering, or innovation/R&D roles.
•Proven track record of taking AI and emerging-technology ideas from concept to production at scale.
•Strong AWS automation and Infrastructure-as-Code expertise.
•Deep hands-on .NET and/or Java development background with strong database engineering skills.
•Demonstrated experience building automation frameworks, mock services, and self-service platforms .
•Strong understanding of microservices, APIs, distributed systems, cloud-native design, and CI/CD practices.
•Excellent leadership, communication, and stakeholder-management skills.
•A builder's mindset—curious, pragmatic, and biased toward rapid experimentation and delivery.
LPL Global Business Services, LLP - PRIVACY POLICY
