Quantiphi

We are looking for a Mid-Level .NET Developer to design, develop, and maintain scalable microservices for enterprise applications. The role involves working on high-performance, reliable systems deployed in containerized environments.

Key Responsibilities:

• Develop and maintain scalable .NET microservices
• Build robust Web APIs with proper validation, error handling, and security
• Write unit and integration tests to ensure code quality
• Design portable and environment-agnostic solutions
• Collaborate with cross-functional teams and client stakeholders
• Optimize performance and implement caching strategies
• Follow security best practices for enterprise applications
• Participate in code reviews and maintain coding standards
• Support deployment and troubleshoot issues in client environments

Must-Have Skills:

Core Technical Expertise:

• 4+ years of experience with .NET Core (3.1+) / .NET 5+ and C# (8+)
• Strong hands-on experience with ASP.NET Core Web API & Entity Framework Core
• Experience building REST APIs and middleware
• Strong understanding of SOLID principles, Dependency Injection, Repository pattern
• Experience with unit testing (xUnit / NUnit / MSTest), Moq, integration testing

Microservices & Deployment:

• Hands-on experience with Docker
• Understanding of microservices architecture & distributed systems
• Experience with configuration management (appsettings.json, IConfiguration)
• Knowledge of NuGet and dependency management

Good-to-Have Skills:

Advanced Technical:

• Experience with .NET 6/7/8, Minimal APIs, gRPC, SignalR
• Advanced EF Core, Dapper, database migrations
• Kubernetes and container orchestration
• Cloud platforms: Azure / GCP / Alibaba Cloud
• Message brokers: Azure Service Bus, RabbitMQ, Kafka
• Databases: PostgreSQL, MySQL, MongoDB, Cassandra
• API Gateways: Azure API Management, Kong

Development & Operations:

• CI/CD tools: Azure DevOps, Jenkins, GitHub Actions
• Monitoring: Application Insights, Serilog, Prometheus
• Security: HTTPS, CORS, input validation, secure coding
• Background services: Hangfire, Quartz.NET

Client-Facing Experience:

• Experience in service-based organizations
• Ability to adapt to multiple domains
• Understanding of industry standards and compliance 

Responsible for developing, enhancing, modifying, and maintaining chatbot applications in the Global Markets environment. The role involves designing, coding, testing, debugging, and documenting conversational AI solutions, along with supporting activities aligned to the corporate systems architecture.

You will work closely with business partners to understand requirements, analyze data, and deliver optimal, market-ready conversational AI and automation solutions.

Key Responsibilities

• Design, develop, test, debug, and maintain chatbot and virtual agent applications
• Collaborate with business stakeholders to define and translate requirements into technical solutions
• Analyze large volumes of conversational data to improve chatbot accuracy and performance
• Develop automation workflows for data handling and refinement
• Train and optimize chatbots using historical chat logs and user-generated content
• Ensure solutions align with enterprise architecture and best practices
• Document solutions, workflows, and technical designs clearly

Required Skills

• Hands-on experience in developing virtual agents (chatbots/voicebots) and Natural Language Processing (NLP)
• Experience with one or more AI/NLP platforms such as:
• Dialogflow, Amazon Lex, Alexa, Rasa, LUIS, Kore.AI
• Microsoft Bot Framework, IBM Watson, Wit.ai, Salesforce Einstein, Converse.ai
• Strong programming knowledge in Python, JavaScript, or Node.js
• Experience training chatbots using historical conversations or large-scale text datasets
• Practical knowledge of:
• Formal syntax and semantics
• Corpus analysis
• Dialogue management
• Strong written communication skills
• Strong problem-solving ability and willingness to learn emerging technologies

Nice-to-Have Skills

• Understanding of conversational UI and voice-based processing (Text-to-Speech, Speech-to-Text)
• Experience building voice apps for Amazon Alexa or Google Home
• Experience with Test-Driven Development (TDD) and Agile methodologies
• Ability to design and implement end-to-end pipelines for AI-based conversational applications
• Experience in text mining, hypothesis generation, and historical data analysis
• Strong knowledge of regular expressions for data cleaning and preprocessing
• Understanding of API integrations, SSO, and token-based authentication
• Experience writing unit test cases as per project standards
• Knowledge of HTTP, REST APIs, sockets, and web services
• Ability to perform keyword and topic extraction from chat logs
• Experience training and tuning topic modeling algorithms such as LDA and NMF
• Understanding of classical Machine Learning algorithms and appropriate evaluation metrics
• Experience with NLP frameworks such as NLTK and spaCy

We are hiring an Associate Technical Architect with strong expertise in Azure-based data platforms to design scalable data lakes, data warehouses, and enterprise data pipelines, while working with global teams.

Key Responsibilities

• Design and implement scalable data lake, data warehouse, and lakehouse architectures on Azure
• Build resilient data pipelines using Azure services
• Architect and optimize cloud-based data platforms
• Improve large-scale data processing and query performance
• Collaborate with engineering teams, QA, product managers, and stakeholders
• Communicate technical roadmap, risks, and mitigation strategies

Must-Have Skills:

• 6+ years of experience in Azure Data Engineering / Data Architecture

Azure Data Platform

• Experience with Azure Data Factory
• Hands-on with Azure Databricks and PySpark
• Experience with Azure Data Lake Storage
• Knowledge of Azure Synapse or Azure SQL for data warehousing

Programming & Data Skills

• Strong programming skills in Python and PySpark
• Advanced SQL with query optimization and performance tuning
• Experience building ETL / ELT data pipelines

Data Architecture Knowledge

• Understanding of MPP databases
• Knowledge of partitioning, indexing, and performance optimization
• Experience with data modeling (dimensional, normalized, lakehouse)

Cloud Fundamentals

• Azure security, networking, scalability, and disaster recovery
• Experience with on-premise to Azure migrations

Certification (Preferred)

• Azure Data Engineer or Azure Solutions Architect certification

Good-to-Have Skills

• Domain experience in FSI, Retail, or CPG
• Exposure to data governance tools
• Experience with BI tools such as Power BI or Tableau
• Familiarity with Terraform, CI/CD pipelines, or Azure DevOps
• Experience with NoSQL databases such as Cosmos DB or MongoDB

Soft Skills

• Strong problem-solving and analytical thinking
• Good communication and stakeholder management
• Ability to translate technical concepts into business outcomes
• Experience working with global or distributed teams

Must have skills:

● Experience: 6+ years of hands-on experience in Cloud Platform Engineering, DevOps, or Site Reliability Engineering (SRE).

● Multi-Cloud Infrastructure: Proficiency in architecting, deploying, and maintaining cloud infrastructure across GCP and Azure (VPC, IAM, Cloud Storage/Blob, Cloud Run/Functions, Pub/Sub, GKE/AKS, Cloud SQL).

● Container Orchestration: Extensive experience with Kubernetes (GKE or AKS) and Docker for managing and scaling containerized applications.

● Infrastructure as Code (IaC) & Automation: Strong proficiency using Terraform along with Python and Bash/Shell scripting for infrastructure automation.

● CI/CD Automation: Experience building and managing CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or ArgoCD.

● Observability & Monitoring: Experience using tools such as Datadog, Prometheus, Grafana, or Splunk for monitoring, logging, and alerting.

● Secrets & Security Management: Experience managing sensitive credentials using HashiCorp Vault, GCP Secret Manager, or Azure Key Vault.

● Architecture & Networking: Understanding of microservices architecture, service-oriented architecture, event-driven systems (Pub/Sub), and cloud networking principles.

Good to have skills:

● AI/ML Infrastructure: Familiarity with infrastructure for ML workloads such as Vertex AI, Azure Machine Learning, GPU node pools, or Vector Databases.

● Advanced Kubernetes: Working knowledge of Kyverno for policy management, Karpenter for cluster autoscaling, or building Kubernetes operators using Go.

● Multi-Cloud Management: Familiarity with Crossplane for managing multi-cloud environments and building cloud-native platforms.

● Cloud Reliability & FinOps: Understanding of disaster recovery, fault tolerance, and cost allocation practices through resource tagging.

● Domain & Compliance: Experience working in regulated environments such as BFSI or Insurance.

Join our core Platform Implementation Team to build intuitive, high-performance user interfaces for a cutting-edge enterprise Data & AI platform. You will develop scalable frontend applications including AI agent marketplaces, operational dashboards, and real-time chat interfaces that integrate seamlessly with backend APIs to support global business units and insurance advisors.

Key Responsibilities

• Design and develop responsive user interfaces for AI-driven applications such as web/app chat interfaces, AI copilots, and personalized content delivery systems.

• Build complex, data-rich dashboards supporting MLOps, GenAIOps, and AgentOps workflows to monitor model performance, manage approval gates, and track infrastructure costs.

• Develop a centralized Agent Marketplace portal for discovering, publishing, and managing reusable AI agents with strict versioning and access controls.

• Integrate frontend applications with APIs to consume reusable AI business services (e.g., document intelligence) and enterprise data products.

• Handle real-time data streams and asynchronous interactions to ensure smooth, low-latency user experiences for chat SDKs and streaming APIs.

• Implement robust state management solutions to support complex user workflows, session states, and multi-step AI agent interactions.

• Optimize frontend performance for high-traffic enterprise applications ensuring fast load times, smooth rendering, and cross-browser/device compatibility.

• Ensure all frontend implementations follow enterprise security standards, data privacy requirements, and WCAG accessibility guidelines relevant to the BFSI sector.

• Collaborate closely with UI/UX designers, backend engineers, integration engineers, and ML architects to bridge design and technical implementation.

• Write and maintain comprehensive unit and integration tests to ensure UI reliability and prevent regressions during continuous deployment cycles.

Must-Have Skills

• Experience with modern frontend frameworks such as React, Next.js, Angular, or Vue.js for building complex SPAs and SSR applications.

• Strong proficiency in JavaScript (ES6+) and TypeScript for writing scalable, maintainable, and type-safe code.

• Familiarity with modern styling approaches such as Tailwind CSS, SASS/LESS, Styled Components, Material UI, Ant Design, or Bootstrap.

• Experience building interfaces for AI/ML platforms, such as chatbot UIs, prompt engineering tools, or complex data visualization dashboards.

• Experience integrating frontend applications with REST APIs, GraphQL, WebSockets, and handling asynchronous data fetching using tools like React Query, SWR, or Axios.

• Familiarity with cloud-native deployment environments such as GCP Cloud Run, Firebase, or Azure Static Web Apps and build tools like Vite or Webpack.

• Hands-on experience with frontend testing frameworks including Jest, React Testing Library, Cypress, or Playwright.

• Experience integrating enterprise Identity and Access Management solutions such as OAuth 2.0, OIDC, or MSAL.

• Understanding of CI/CD pipelines for frontend applications and automated deployment workflows.

Good to Have

• Experience in the Life Insurance or broader BFSI domain with familiarity with user personas such as insurance agents, underwriters, or policyholders.

This role is responsible for architecting and implementing the Agentic capabilities of the PHI ecosystem. The engineer will lead the development of multi-agent systems, enabling seamless interoperability between AI agents, internal tools, and external services.

The position requires a strong focus on AI safety, secure agent orchestration, and tool-connected AI systems capable of executing complex workflows within the health insurance domain.

1. Agent Orchestration

• Build and manage autonomous AI agents using Agent Development Kit (ADK) and Vertex AI Agent Engine.
• Design and implement multi-agent workflows capable of handling complex tasks.

2. Interoperability

• Implement the Model Context Protocol (MCP) to enable connectivity between:
• AI agents
• Internal PHI tools
• External services and APIs.

3. Multimodal Development

• Build real-time, bidirectional audio applications using the Gemini Live API.
• Integrate image generation models and support multimodal AI capabilities.

4. Safety Engineering

• Implement AI safety layers to protect sensitive healthcare data.
• Use Model Armor and Cloud DLP API to:
• Sanitize prompts
• Prevent exposure of PII/PHI data
• Enforce secure AI interactions.

5. Agent-to-Agent (A2A) Communication

• Configure remote agent connectivity using the A2A SDK.
• Enable cross-agent collaboration and workflow orchestration.

Must-Have Skills

• Advanced proficiency with Agent Development Kit (ADK).
• Strong experience with Vertex AI Agent Engine.
• Hands-on experience with Model Context Protocol (MCP).
• Experience implementing Agent-to-Agent (A2A) workflows using the A2A SDK.
• Expertise in Google Gen AI SDK for Python.
• Experience building multimodal AI applications.
• Proven experience implementing AI safety layers, including:
• Model Armor
• Cloud DLP API

Good-to-Have Skills (Foundation)

Data & Analytics

• BigQuery optimization techniques, including:
• Partitioning
• Clustering
• Denormalization for performance and cost optimization.

Streaming & Real-Time Pipelines

• Experience building real-time data pipelines using:
• Google Pub/Sub
• BigQuery streaming pipelines

We are seeking a Senior Machine Learning Engineer to support the development and deployment of advanced AI capabilities within the PHI ecosystem.

This role focuses on the execution of Generative AI tasks, including model integration and agent deployment. The candidate will be responsible for building RAG-based workflows and ensuring AI interactions remain grounded and accurate using Google Cloud AI tools.

Key Responsibilities

1. GenAI Integration

• Develop and maintain integrations with Gemini 1.5 Pro and Flash models
• Use the Google Gen AI SDK for Python to build and manage model integrations

2. Agent Deployment

• Assist in deploying AI agents to Vertex AI Agent Engine
• Work with the Agent Development Kit (ADK) for agent lifecycle management

3. RAG & Embeddings

• Generate and manage text and multimodal embeddings
• Support semantic search and Retrieval-Augmented Generation (RAG) pipelines

4. Testing & Quality

• Run evaluation scripts to verify model output quality
• Ensure models follow grounding and response accuracy guidelines

Must-Have Skills

• Strong Python programming
• Experience working with REST APIs
• Hands-on experience with Vertex AI Studio
• Experience working with Gemini APIs
• Understanding of Agentic AI concepts
• Familiarity with ADK CLI
• Experience or understanding of RAG architecture
• Knowledge of embedding generation

Good-to-Have Skills (Foundation):

BigQuery

• Basic SQL knowledge
• Experience with data loading
• Ability to debug and troubleshoot queries

Data Streaming

• Familiarity with Google Pub/Sub
• Understanding of synthetic data generation

Visualization

• Basic reporting and dashboards using Looker Studio

As a Backend Engineer, you will be a core member of the Platform Implementation Team, responsible for building the robust, scalable, and secure backend infrastructure for a multi-cloud enterprise Data & AI platform.

You will design and develop high-performance microservices, RESTful APIs, and event-driven architectures that serve as the backbone for enterprise-wide applications.

Working closely with Platform Engineers, Data Modelers, and UI teams, you will ensure seamless data flow between core business systems (CRM, ERP) and the platform, enabling the rollout of critical business services across multiple global Local Business Units (LBUs).

Backend Development

• Design and develop scalable backend services and microservices
• Build and maintain RESTful APIs for enterprise applications
• Define and maintain API contracts using OpenAPI/Swagger

Platform & System Integration

• Enable seamless integration between enterprise systems (CRM, ERP) and the platform
• Support data flow across multiple global business units

Event-Driven Architecture

• Implement asynchronous processing and event-driven systems
• Work with message brokers and streaming platforms

Cross-Functional Collaboration

• Collaborate with platform engineers, data modelers, and frontend teams
• Contribute to architecture discussions and backend design decisions

Must-Have Skills

Experience

• 5–7 years of hands-on experience in backend software engineering
• Experience building enterprise-grade backend systems

Core Programming

Strong proficiency in at least one backend language:

• Python
• Node.js
• Java

Strong understanding of:

• Object-oriented programming (OOP)
• Functional programming principles

API & Microservices

• Extensive experience building RESTful APIs
• Experience designing microservices architectures
• Ability to define API contracts using OpenAPI / Swagger

Cloud Infrastructure

Hands-on experience with cloud platforms:

• Google Cloud Platform (GCP)
• Microsoft Azure

Examples of services:

• Cloud Functions
• Cloud Run
• Azure App Services

Database Management

Experience with both Relational and NoSQL databases

Relational:

• PostgreSQL
• Cloud SQL

NoSQL:

• Schema design
• Complex querying
• Performance optimization

Event-Driven Architecture

Experience with asynchronous processing and message brokers:

• GCP Pub/Sub
• Apache Kafka
• RabbitMQ

Security & Authentication

Strong understanding of:

• OAuth 2.0
• JWT authentication
• Role-Based Access Control (RBAC)
• Data encryption

Software Engineering Best Practices

• Writing clean, maintainable code
• Version control using Git
• Writing unit and integration tests
• Familiarity with CI/CD pipelines
• Containerization using Docker

Good-to-Have Skills

AI & LLM Integration

• Experience integrating Generative AI models
• Exposure to:
• OpenAI
• Vertex AI
• LLM gateways
• Retrieval-Augmented Generation (RAG)

Frontend Exposure

Basic familiarity with frontend frameworks such as:

• React
• Next.js
• Angular

Understanding how backend APIs integrate with UI applications

Advanced Data Stores

Experience with:

• Vector databases (Pinecone, Milvus)
• Knowledge graphs

Domain Knowledge

• Experience in Life Insurance or BFSI sector
• Understanding of enterprise data governance and compliance standards

We are seeking a highly skilled Senior Backend Developer with deep expertise in Python and FastAPI to join our team. This role focuses on building high-performance, scalable backend services capable of handling high request volumes while integrating advanced LLM technologies.

The ideal candidate will design robust distributed systems, implement efficient data storage solutions, and ensure enterprise-grade security within an Azure-based infrastructure. This is a great opportunity to work on AI/ML integrations and mission-critical applications requiring high performance and reliability.

Key Responsibilities:

Backend Development

• Design and maintain high-performance backend services using Python and FastAPI
• Implement advanced FastAPI features such as dependency injection, middleware, and async programming
• Write comprehensive unit tests using pytest
• Design and maintain Pydantic schemas

High-Concurrency Systems

• Implement asynchronous code for high-volume request processing
• Apply concurrency patterns and atomic operations to ensure efficient system performance

Data & Storage

• Optimize MongoDB operations
• Implement Redis caching strategies (TTL, performance tuning, caching patterns)

Distributed Systems

• Implement rate limiting, retry logic, failover mechanisms, and region routing
• Build microservices and event-driven architectures
• Work with EventHub, Blob Storage, and Databricks

AI/ML Integration

• Integrate OpenAI API, Gemini API, and Claude API
• Manage LLM integrations using LiteLLM
• Optimize AI service usage within the Azure ecosystem

Security

• Implement JWT authentication
• Manage API keys and encryption protocols
• Implement PII masking and data security mechanisms

Collaboration

• Work with cross-functional teams on architecture and system design
• Contribute to engineering best practices and technical improvements
• Mentor junior developers where required

Must-Have Skills & Requirements

Experience

• 7+ years of hands-on Python backend development
• Bachelor’s degree in Computer Science, Engineering, or related field
• Experience building high-traffic, scalable systems

Core Technical Skills

Python

• Advanced knowledge of asynchronous programming, concurrency, and atomic operations

FastAPI

• Expert-level experience with dependency injection, middleware, and async code

Testing

• Strong experience with pytest and Pydantic schemas

Databases

• Hands-on experience with MongoDB and Redis
• Strong understanding of caching patterns, TTL, and performance optimization

Distributed Systems

• Experience with rate limiting, retry logic, failover mechanisms, high concurrency processing, and region routing

Microservices

• Experience building microservices and event-driven systems
• Exposure to EventHub, Blob Storage, and Databricks

Cloud

• Strong experience working in Azure environments

AI Integration

• Familiarity with OpenAI API, Gemini API, Claude API, and LiteLLM

Security

• Implementation experience with JWT authentication, API keys, encryption, and PII masking

Soft Skills

• Strong problem-solving and debugging skills
• Excellent communication and collaboration
• Ability to manage multiple priorities
• Detail-oriented approach to code quality
• Experience mentoring junior developers

Good-to-Have Skills

Containerization

• Docker, Kubernetes (preferably within Azure)

DevOps

• CI/CD pipelines and automated deployment

Monitoring & Observability

• Experience with Grafana, distributed tracing, custom metrics

Industry Experience

• Experience in Insurance, Financial Services, or regulated industries

Advanced AI/ML

• Vector databases
• Similarity search optimization
• LangChain / LangSmith

Data Processing

• Real-time data processing and event streaming

Database Expertise

• PostgreSQL with vector extensions
• Advanced Redis clustering

Multi-Cloud

• Experience with AWS or GCP alongside Azure

Performance Optimization

• Advanced caching strategies
• Backend performance tuning

Role & Responsibilities

• Develop and deliver automation software to build and improve platform functionality
• Ensure reliability, availability, and manageability of applications and cloud platforms
• Champion adoption of Infrastructure as Code (IaC) practices
• Design and build self-service, self-healing, monitoring, and alerting platforms
• Automate development and testing workflows through CI/CD pipelines (Git, Jenkins, SonarQube, Artifactory, Docker containers)
• Build and manage container hosting platforms using Kubernetes

Requirements

• Strong experience deploying and maintaining GCP cloud infrastructure
• Well-versed in service-oriented and cloud-based architecture design patterns
• Knowledge of cloud services including compute, storage, networking, messaging, and automation tools (e.g., CloudFormation/Terraform equivalents)
• Experience with relational and NoSQL databases (Postgres, Cassandra)
• Hands-on experience with automation/configuration tools (Puppet, Chef, Ansible, Terraform)

Additional Skills

• Strong Linux system administration and troubleshooting skills
• Programming/scripting exposure (Bash, Python, Core Java, or Scala)
• CI/CD pipeline experience (Jenkins, Git, Maven, etc.)
• Experience integrating solutions in multi-region environments
• Familiarity with Agile/Scrum/DevOps methodologies