ResponsibilitiesSit with a business or clinical leader and reframe an idea or problem into something concrete and buildable. Know what to build by the end of the conversation; have a working prototype to react to by the end of the week. Partner closely with product, design, and client stakeholders to translate ambiguous ideas into software that ships. Demo live without a slide deck. Reframe problems out loud. Don't get stuck waiting for someone else to make the decision. Lead POCs, innovation sprints, and internal research experiments to validate emerging AI techniques. Build (fast) with AI When the brief is clear, head down and produce. Build modular backends in Python or TypeScript aligned with clean architecture, OOP, SOLID, and domain-driven design. Create fullstack applications, APIs, agents, workflows, and similar systems using frameworks such as Next.js, React, FastAPI, Fastify, FastMCP, and Hono. Architect and ship production-grade agentic applications using LangGraph, AutoGen, Claude Agent SDK, OpenAI Assistants, or your own orchestration layer. Integrate frontier and self-hosted LLMs (Claude, GPT, Gemini, open-weight models) with tools, data, and external systems through MCP and custom connectors. Apply RAG techniques where they actually help: vector databases (Pinecone, Chroma, Weaviate, pgvector), hybrid retrieval with ElasticSearch or Solr, and BM25 + similarity search. Work across relational, document, key-value, and graph stores as the problem demands; use event-driven patterns where they fit, not by default. Design prompt and context engineering frameworks that optimize accuracy, repeatability, cost, and latency. Use AI-assisted development tools (Claude Code, GitHub Copilot, Cursor, Codex) through structured workflows, native instructions, templates, and sub-agents—with discipline and review. Fine-tune or adapt models where the problem genuinely calls for it. Test, Deploy, Productionize Spin up the infra, write the evals, wire up the MCP servers, deploy the agents, and harden the bits that survive contact with real users. Deploy on AWS, Azure, Cloudflare, or Vercel using containerization (Docker, Kubernetes) or serverless—chosen for fit, not preference. Treat evals as a first-class discipline: hands-on harnesses, not theoretical frameworks. Build with a clear-eyed view of where current AI tooling helps and where it falls short. Apply engineering practices that hold up in production: TDD, secrets management and rotation, SAST/DAST, structured logging, metrics, tracing, and automated CI/CD (GitHub Actions, Jenkins). Own what you build end-to-end, including the infrastructure and operations that keep it running. Mentor others on system design, agentic patterns, and AI engineering best practices. Qualification & Experience 3+ years relevant experience building production applications using AI / agentic development approaches-fullstack applications, agents, workflows, MCPs, and more. Hands-on experience with agents, not just prompted models. You have wired tools to a model and let it run multi-step using LangGraph, AutoGen, Claude Agent SDK, OpenAI Assistants, or your own orchestration. Active, structured use of AI-assisted development tools (Claude Code, Cursor, GitHub Copilot) with demonstrable workflows, sub-agents, skills, and innovative approaches. Strong Python or TypeScript, with OOP, SOLID, 12-factor application development, and microservice architecture. You've built Next.js applications, FastAPI services, and similar. End-to-end implementation experience with vector databases, retrieval pipelines, and eval harnesses. Cloud-native deployment experience across at least one of AWS, Azure, Cloudflare, or Vercel-with Docker, Kubernetes, and GitHub Actions. A no-compromise attitude on clean code, TDD, security, observability, scalability, performance, and cost. A deep working understanding of how LLMs behave-and where they break-and how to optimize accuracy, latency, and cost. Clear writing and a willingness to reframe problems in conversation rather than wait for someone else to define them. A real, recent trail of built things: GitHub, a portfolio, side projects, indie tools, or OSS contributions. A founder's mindset and genuine appetite for ambiguous, high-impact technical challenges. Bachelor's or Master's in Computer Science, Machine Learning, or a related technical discipline. Public writing, talks, or threads about building with AI. MLOps and model serving experience (BentoML, MLflow, Vertex AI, SageMaker). Streaming and batch ingestion pipelines (Spark, Airflow, Beam, Glue). Healthcare or life sciences domain exposure. AWS Professional certification or other relevant industry certifications. 

Qualification & ExperienceCan build an automation framework. Have 3+ years of experience in automation. Well versed with selenium. Well versed with any programming language: Kotlin or Java Guide the developers on Unit and Integration Testing Have a good understanding of behavior driven development. Have 1+ years of experience in service-virtualization. Build and Deployment automation Identify cases that should be tested manually. Apply analytical and logical thinking to discover edge cases Organize test specifications according to impact, component, likelihood, etc Help the Product Manager with writing Acceptance Criteria that can be part of the living Documentation

ResponsibilitiesDesign, develop, and maintain backend systems using Kotlin, Micronaut & Spring Cloud Work closely with other engineers to ensure that our systems are scalable, reliable, and secure Implement unit tests and TDD (test-driven development) to ensure the quality of our code Participate in the design and implementation of new features Work with other teams to integrate our backend systems with other systems in our ecosystemQualification & Experience 2+ years of experience in developing backend systems using Kotlin, Micronaut, Spring Cloud, or other similar technologies  Strong understanding of unit testing and TDD  Experience with DDD (domain-driven design), CQRS, Clean Architecture, Hexagonal Architecture, Microservices, Multi tenancy and Event Sourcing is a plus Excellent problem-solving and analytical skills Ability to work independently and as part of a team Strong communication and interpersonal skills Experience in developing backend systems for fintech companiesExperience in developing backend systems for b2b enterprise SaaS product. Experience with cloud computing platforms such as Azure Experience with Docker and Kubernetes 

ResponsibilitiesLead and mentor a team of backend engineers Design, develop, and maintain highly scalable and reliable backend applications Work with a team of engineers to implement new features and improve existing ones Have deep knowledge of software architecture principles and best practices Participate in the system design process and contribute to the overall architecture of the backend system Write clean, maintainable, and efficient code following best practices and coding standards Collaborate with frontend developers and UI/UX designers to ensure seamless integration between the frontend and backend Conduct thorough testing and debugging of the backend code Stay up-to-date with the latest industry trends and technologies, and proactively suggest improvements to enhance the backend infrastructure Manage PODs and set goals for the team Conduct performance reviews and provide feedback to team members Unit Testing: Strong understanding of unit testing principles and practices Experience using a unit testing framework such as Jest or JUnit Experience writing unit tests for both Node.js and Java code Experience using TDD to build softwareQualification & ExperienceBachelor's degree in Computer Science or a related field 6-8 years of experience in backend development Strong experience with Node.js, TypeScript, NestJS, PostgreSQL, and Azure Experience with Java and Kotlin is a plus Experience leading and mentoring a team of engineers Strong problem-solving and analytical skills Excellent communication and collaboration skills

Responsibilities• Design, develop, and deploy production-grade Generative AI solutions including LLM integrations, RAG pipelines, AI agents, and prompt engineering frameworks.• Build and optimize applications using foundation models (OpenAI GPT-4/o, Anthropic Claude, Gemini, Mistral, Llama, etc.) via API or self-hosted deployment.• Implement vector databases (Pinecone, Weaviate, Qdrant, pgvector) and embedding strategies for semantic search and retrieval.• Develop and manage LangChain, LlamaIndex, or custom orchestration frameworks for multi-step AI workflows.• Integrate AI capabilities with existing enterprise systems, APIs, and data pipelines.• Ensure models are fine-tuned, evaluated, and monitored for accuracy, safety, latency, and cost.• Tech Lead Responsibilities• Lead end-to-end technical design and architecture of GenAI systems with a focus on scalability and maintainability.• Define best practices, coding standards, and review processes for the GenAI engineering workstream.• Mentor and guide junior/mid-level developers on GenAI concepts, tooling, and implementation.• Collaborate with product, data science, and platform teams to translate business requirements into technical solutions.• Conduct technical interviews and evaluate third-party AI tools and vendors as needed.• Prepare and present technical proposals, architecture decision records (ADRs), and engineering roadmaps.• MLOps & Infrastructure• Design and implement CI/CD pipelines for AI model deployment on cloud platforms (AWS, GCP, Azure).• Set up evaluation harnesses, A/B testing frameworks, and observability tooling (LangSmith, Helicone, Arize, etc.).• Manage containerization and orchestration (Docker, Kubernetes) for AI microservices.• Implement guardrails, rate limiting, cost tracking, and latency monitoring for LLM APIs.Qualification & Experience • Strong proficiency with OpenAI, Anthropic, Google, Mistral, or Cohere APIs LLM APIs: • LangChain, LlamaIndex, Semantic Kernel, or equivalent orchestration tools Frameworks: • Pinecone, Weaviate, Qdrant, Chroma, or pgvector Vector Databases: • Python (primary); TypeScript/Node.js desirable Languages: • At least one of AWS (Bedrock, SageMaker), GCP (Vertex AI), or Azure (OpenAI Service) Cloud: • Docker, Kubernetes, GitHub Actions / GitLab CI, model serving (FastAPI, vLLM, Triton) MLOps: • LangSmith, Helicone, Arize AI, Weights & Biases, or similar Observability: • Experience with fine-tuning (LoRA, QLoRA, RLHF) on open-source models (Llama, Mistral, Phi)• Knowledge of AI safety, responsible AI principles, and content moderation approaches • Familiarity with multi-modal models (vision-language, audio-to-text) • Experience with graph databases (Neo4j) and knowledge graph integration • Prior Tech Lead or Staff Engineer experience in a product engineering environment

Responsibilities Expected to be an SME, collaborate and manage the team to perform.  Responsible for team decisions.  Engage with multiple teams and contribute on key decisions.  Provide solutions to problems for their immediate team and across multiple teams.  Facilitate regular meetings to ensure alignment and address any challenges that may arise.  Develop and maintain comprehensive project documentation to track progress and outcomes.Experience The candidate should have minimum 5 years of experience in Program Project Management.  A 15 years full time education is required.

ResponsibilitiesWebsite & Landing Page Development Build and maintain: Marketing website pages on WordPress with Elementor and custom PHP templates Campaign landing pages with form integrations (Gravity Forms, HubSpot, etc.) Microsites for events and campaigns Ensure pages are: High-performing and optimized for speed Mobile responsive across all devices and screen sizes Conversion-optimized with clear CTAs and lead capture flows Manage deployments on AWS Cloud infrastructure (EC2, CloudFront, S3) Growth & Conversion Optimization Work with marketing team to: A/B test landing pages Improve conversion rates Optimize user journeys Implement tracking, forms, and integrations for lead capture Set up and maintain Google Analytics, Google Tag Manager, and event tracking AI-Assisted Web Development Use tools like: Claude, ChatGPT, GitHub Copilot, Cursor Lovable, Webflow AI, Framer AI Generate, optimize, and iterate website components using AI Build faster using AI-assisted workflows for code generation, debugging, and documentation Agentic AI & Automation Experiment with: AI agents for website updates and content deployment Automated page creation workflows Content-to-page pipelines Build systems that allow marketing teams to scale website creation without developer dependency Collaboration with Marketing Work closely with: Demand generation Content Design teams Translate campaign requirements into live web experiences quickly Participate in code reviews and contribute to technical discussions on WebDev productivity Qualification & Experience Strong inclination toward Agentic AI Already using AI tools for coding, building websites, and automating workflows Builder mindset — enjoys creating and shipping fast High ownership, bias toward action, and drive Coachable and adaptable in a fast-paced environment Technical Skills (Basic Expectation) Frontend: HTML, CSS, JavaScript (React is a plus) CMS & Page Building: WordPress, Elementor (hands-on experience preferred) Backend: PHP fundamentals (custom templates, shortcodes, hooks) Cloud & Hosting: Familiarity with AWS Cloud (EC2, S3, CloudFront) or similar hosting environments Understanding of: Landing pages, forms, APIs, and integrations Databases (SQL and/or NoSQL basics) Basic SEO principles and web performance optimization

Responsibilities Processing monetary and non-monetary transactions for assigned clients ransactions. Includes Contributions, loan repayments, Indicative data files and manual adjustments, Rollovers etc.  Ensures all items are processed and\or resolved in a time. Supports business in ensuring positive audit results  Complies with all client policies, procedures, and Federal/State/Local regulations and escalates issues to the management.  Perform research on all processing irregularities and drive issues to resolution What are we looking for? "Must have/ minimum requirement Open core Night shifts based on business requirements  Good verbal & written communication skills  Good typing skill and attention to detail.  Good time management skillsQualification & Experience 3+ years of experience in US Retirement Services domain – Defined Contributions - Managing participant level services  Experience in Money In processes such as Contributions processing, loan repayments, Indicative data files and manual adjustments, Rollovers contribution, Suspense & Adjustments/Corrections. Skillset:  Bachelors’ degree  Experience in the US retirement industry

ResponsibilitiesPerform functional, regression, and integration testing of IVR systems and Java-based backend services. Design and execute test cases and test scripts for end-to-end IVR call flow testing.Conduct performance and load testing of IVR systems using JMeter.Perform manual testing for new call flows, voice prompts, and routing logic.Validate IVR behavior, DTMF input handling, and call transfer scenarios.Collaborate with development and operations teams to troubleshoot issues and verify defect fixes.Document test results, defects, and prepare test summary reports. Experience The candidate should have minimum 5 years of experience in Program Project Management.  A 15 years full time education is required.

Responsibilities Manages databases through multiple product lifecycle environments, from development to mission critical production systems. Applies data modeling techniques to ensure development and implementation support efforts meet integration and performance expectations. Independently analyzes, solves, and corrects issues in real time, providing problem resolution end-to-end. Refines and automates regular processes, tracks issues, and documents changes. Assists developers with complex query tuning and schema refinement. Provides 24x7 support for critical production systems. Participates in an On-Call rotation as needed Performs scheduled maintenance and support release deployment activities after hours. Shares domain and technical expertise, providing technical mentorship and cross training to other peers and team members. Installs, configures, patches, and upgrades database servers. Manages on-prem and cloud based (Azure-preferred) database servers and services in PaaS and IaaS cloud solutions.Experience6+ years SQL Database Server Administration experience Monitoring software systems to detect potential database problems. Investigating, troubleshooting, and evaluation of Production database problems. Recommending and implementing approved solutions and documents the problem / resolution. Writing, testing, and implementing operating system scripts and procedures to automate various SQL DBA functions and processes. Coordinating development, testing, and implementation of database systems to meet database capacity standards and sizing objectives.