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Sr. Data Engineer (PySpark & Python + AI Tools Exp.) - (Only W2 or 1099)
Charlotte, NC (Hybrid)
12+ Months Contract
Job Description:
We are currently seeking a Senior Data Engineer with hands-on coding experience and a strong background in Python, PySpark, and Object-oriented programming.
The ideal candidate will be responsible for designing, developing, and implementing new features to our existing framework using PySpark and Python.
This position requires a deep understanding of data transformation and the ability to create standalone scripts based on given business logic. Also, exposure to AI Tools and building any AI applications will be advantage.
Key Responsibilities:
- Design, develop, and optimize large-scale data pipelines using PySpark and Python.
- Implement and adhere to best practices in object-oriented programming to build reusable, maintainable code.
- Write advanced SQL queries for data extraction, transformation, and loading (ETL).
- Collaborate closely with data scientists, analysts, and stakeholders to gather requirements and translate them into technical solutions.
- Troubleshoot data-related issues and resolve them in a timely and accurate manner.
- Leverage AWS cloud services (e.g., S3, EMR, Lambda, Glue) to build and manage cloud-native data workflows (preferred).
- Participate in code reviews, data quality checks, and performance tuning of data jobs.
Required Skills & Qualifications:
- 6+ years of relevant experience in a data engineering or backend development role.
- Strong hands-on experience with PySpark and Python, especially in designing and implementing scalable data transformations.
- Solid understanding of Object-Oriented Programming (OOP) principles and design patterns.
- Proficient in SQL, with the ability to write complex queries and optimize performance.
- Strong problem-solving skills and the ability to troubleshoot complex data issues independently.
- Excellent communication and collaboration skills.
- Hands-on experience with AI Tools.
Preferred Qualifications (Nice to Have):
- Experience working with AWS cloud ecosystem (S3, Glue, EMR, Redshift, Lambda, etc.).
- Exposure to data warehousing concepts, distributed computing, and performance tuning.
- Familiarity with version control systems (e.g., Git), CI/CD pipelines, and Agile methodologies.
- Exposure to AI Tools and hands-on experience of building any AI applications.
Job Title: Senior Automation Engineer
Location: Hillsboro, Oregon
Job Type: Full-Time
Job Description:
We are seeking a highly experienced Senior Automation Engineer to join our advanced software and embedded systems team. The ideal candidate will have deep expertise in Python automation (Pytest), Robot Framework, and QNX environments, with strong skills in UX/UI automation and testing. This role involves enhancing and migrating automation frameworks, debugging complex integrations, and working closely with cross-functional teams to deliver high-quality test automation solutions for embedded systems and entertainment platforms.
Key Responsibilities
Automation Framework Development
- Architect, develop, and maintain automation frameworks primarily using Python and Pytest.
- Lead migration of existing Robot Framework tests to Python/Pytest equivalents.
- Build reusable fixtures, utilities, wrapper layers, and automation components to support large test suites.
Test Execution & Optimization
- Analyze and interpret Robot Framework keyword libraries; enable efficient reuse within Python-based executions.
- Optimize hybrid execution flows involving both Pytest and Robot Framework assets.
- Execute and maintain UI and device automation tests using tools such as Appium, Selenium, or equivalent frameworks.
Cross-Layer Debugging & Integration
- Independently debug cross-layer automation issues involving Python, Robot Framework, device tools, and operating systems.
- Integrate automation frameworks with CI/CD pipelines and tools (e.g., Jenkins, GitLab, Azure DevOps).
Collaboration & Mentorship
- Mentor and guide junior automation engineers, establishing good coding practices, test design patterns, and quality standards.
- Work collaboratively with software engineers, product developers, and QA teams to enhance automation coverage and reliability.
System & Environment Interaction
- Work with QNX OS, virtualization systems (Hypervisor), and cloud environments (AWS).
- Engage with hardware interfacing (USB, Ethernet, multimedia interfaces) and hardware simulation/ fault-injection where applicable (nice-to-have).
Required Skills & Experience
- 7–10 years experience in automation engineering with 5+ years hands-on Python automation using Pytest.
- Practical experience with Robot Framework including keywords, variables, resources, and large keyword repositories.
- Strong skills in UI automation using tools such as Appium/Selenium.
- Solid understanding of modular test design and maintainable patterns (page-object, keyword patterns).
- Experience with QNX (Posix) operating system, virtualization (e.g., Hypervisor), and cloud-based environments (preferably AWS).
- Good understanding of Git, branching strategies, and CI/CD workflows.
- Proven ability to debug complex, multi-layered test automation environments.
Preferred Qualifications
- Exposure to embedded systems, aviation, or high-volume regression environments.
- Experience in framework migration, cross-framework interoperability, or keyword reuse models.
- Background in hardware interactions and media/UX systems (multimedia I/O, touch interactions).
- Familiarity with fault injection tools and hardware simulation techniques.
- Bachelor’s degree in Computer Science, Electronics, or related technical field.
Nice-to-Have Skills
- Hardware interfacing (USB, Ethernet), multimedia interfaces (touch, audio/video).
- Fault-injection and hardware simulation experience.
- Knowledge of peripheral communication protocols (e.g., GMSL, IP).
Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA
Title: Machine Learning Engineer
Location: San Jose, CA
Responsibilities:
- Productize and optimize models from Research into reliable, performant, and cost-efficient services with clear SLOs (latency, availability, cost).
- Scale training across nodes/GPUs (DDP/FSDP/ZeRO, pipeline/tensor parallelism) and own throughput/time-to-train using profiling and optimization.
- Implement model-efficiency techniques (quantization, distillation, pruning, KV-cache, Flash Attention) for training and inference without materially degrading quality.
- Build and maintain model-serving systems (vLLM/Triton/TGI/ONNX/TensorRT/AITemplate) with batching, streaming, caching, and memory management.
- Integrate with vector/feature stores and data pipelines (FAISS/Milvus/Pinecone/pgvector; Parquet/Delta) as needed for production.
- Define and track performance and cost KPIs; run continuous improvement loops and capacity planning.
- Partner with ML Ops on CI/CD, telemetry/observability, model registries; partner with Scientists on reproducible handoffs and evaluations.
Educational Qualifications:
- Bachelors in computer science, Electrical/Computer Engineering, or a related field required; Master’s preferred (or equivalent industry experience).
- Strong systems/ML engineering with exposure to distributed training and inference optimization.
Industry Experience:
- 3–5 years in ML/AI engineering roles owning training and/or serving in production at scale.
- Demonstrated success delivering high-throughput, low-latency ML services with reliability and cost improvements.
- Experience collaborating across Research, Platform/Infra, Data, and Product functions.
Technical Skills:
- Familiarity with deep learning frameworks: PyTorch (primary), TensorFlow.
- Exposure to large model training techniques (DDP, FSDP, ZeRO, pipeline/tensor parallelism); distributed training experience a plus
- Optimization: experience profiling and optimizing code execution and model inference: (PTQ/QAT/AWQ/GPTQ), pruning, distillation, KV-cache optimization, Flash Attention
- Scalable serving: autoscaling, load balancing, streaming, batching, caching; collaboration with platform engineers.
- Data & storage: SQL/NoSQL, vector stores (FAISS/Milvus/Pinecone/pgvector), Parquet/Delta, object stores.
- Write performant, maintainable code
- Understanding of the full ML lifecycle: data collection, model training, deployment, inference, optimization, and evaluation.
Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA
Remote working/work at home options are available for this role.
We are seeking a Senior Lead Developer to lead the development and deployment of our backend services. In this role, you will be the bridge between our PostgreSQL database and React frontend, responsible not only for writing high-performance Python code but also for architecting the CI/CD pipelines that bring our applications to life. You will ensure our integration layers are scalable, secure, and automatically deployed.
Key Responsibilities
• API & Backend Development: Design and maintain production-grade RESTful APIs using Python (FastAPI, Flask) with a focus on asynchronous processing.
• Database Engineering: Architect relational schemas and write optimized SQL in PostgreSQL, ensuring data integrity and query performance.
• React Integration: Partner with frontend teams to define API contracts, handle state-consistent data fetching, and implement secure authentication (JWT/OAuth2).
• CI/CD & Deployment: Build and manage automated deployment pipelines (e.g., Azure DevOps or Jenkins) to move code from local environments to staging and production.
• Containerization & Cloud: Package applications using Docker and manage deployments on cloud platforms or container orchestrators (Kubernetes/ECS).
• System Reliability: Implement automated testing (PyTest), logging, and monitoring to ensure high availability of integration services.
Technical Requirements
• Experience: 10+ years of professional backend development with a heavy emphasis on Python and API architecture.
• PostgreSQL Expert: Advanced SQL knowledge, including indexing strategies, migrations (Alembic/Flyway), and performance profiling.
• DevOps Tooling: Hands-on experience with Docker and building CI/CD pipelines for Python applications.
• Frontend Literacy: Solid understanding of React (Hooks, Context API) and how it consumes complex JSON structures.
• Infrastructure as Code (Bonus): Familiarity with Terraform or AWS CloudFormation is a significant plus.
The "Lead" Expectation
At the 10-year mark, we expect more than just "feature delivery." We are looking for a candidate who:
• Automates Everything: If a task is done twice, they write a script or a CI job for it.
• Designs for Failure: Implements proper error handling, retries, and health checks in the API layer.
• Collaborates Across the Stack: Can jump into a React component or a Postgres execution plan to find the root cause of a bottleneck.
Must be local to TX
Role Overview
- He’s ideally looking for someone with 13+ years of experience, strong architecture depth, and the ability to clearly explain designs.
- Must have experience using AI is used in day‑to‑day development.
- Must have experience as a API Developer to lead the development and deployment of our backend services. In this role, you will be the bridge between our PostgreSQL database and React frontend, responsible not only for writing high-performance Python code but also for architecting the CI/CD pipelines that bring our applications to life. You will ensure our integration layers are scalable, secure, and automatically deployed.
Job Summary
We are seeking a Principal-level Full Stack Lead Developer with 13+ years of experience to drive high-priority engineering workstreams. This role is for a technical heavyweight who can lead new projects in parallel with existing leadership while maintaining exceptional architecture depth. You will be responsible for the full lifecycle of high-performance FastAPI and React applications, ensuring they are resilient, observable, and scalable. We expect a leader who views AI development tools as a force multiplier for velocity and can clearly articulate complex design decisions to stakeholders.
Key Responsibilities
- Project Sovereignty: Independently lead and deliver new, complex workstreams from inception to launch, acting as a technical peer to existing leadership (e.g., Sai).
- System Architecture: Design and defend distributed microservices and event-driven architectures. You must be able to clearly whiteboard and communicate design patterns to both technical and non-technical audiences.
- Hands-on Execution: Maintain high-velocity output of clean, production-grade code using FastAPI (Python) and React (TypeScript).
- Platform Reliability: Architect and implement global Error Handling frameworks, centralized Logging (e.g., OpenTelemetry, ELK), and API Management strategies including Rate Limiting and versioning.
- Event-Driven Messaging: Oversee the implementation of asynchronous service communication using ActiveMQ or AWS EventBridge.
- AI-Augmented SDLC: Deeply integrate AI coding tools (e.g., CloudCode, Cursor, GitHub Copilot) into daily workflows to accelerate prototyping, refactoring, and automated testing.
- Engineering Mentorship: Foster a culture of excellence through rigorous code reviews and by unblocking senior engineers on complex technical hurdles.
- Product Collaboration: Work closely with Product Managers to turn high-level roadmaps into technical reality, providing accurate estimates and identifying technical risks early.
Required Skills & Qualifications
- Experience:13+ years of professional software development with a proven track record of leading large-scale products.
- Tech Stack Mastery: Expert-level FastAPI (Async Python) and modern React (Hooks, TypeScript, Performance Profiling).
- Advanced Governance: Hands-on experience with API Gateway patterns, request throttling, and securing distributed systems (OAuth2/JWT).
- Observability & Messaging: Deep knowledge of structured logging, distributed tracing, and message brokers (ActiveMQ or EventBridge).
- AI Tooling: Advanced proficiency in using AI tools for Fast Development to reduce manual overhead and multiply team output.
- Database & Infrastructure: Expert-level PostgreSQL (tuning/indexing), Redis (for caching/rate-limiting), and container orchestration (Kubernetes/Docker).
- Communication: Exceptional ability to translate technical "scars" and architectural risks into clear business impact.
Job Role: Lead Software Engineer - AI Application Platform
Location: Charlotte, NC (Onsite)
Eligibility: USC/GC/H4-EAD only
Pay Rate: $90/hr. on W2
The Opportunity
We are seeking a Lead Software Engineer to guide the architectural development and execution of AppGen, a sophisticated AI-powered application generation platform. This role suits a proven technical leader with deep, hands-on expertise across the full software stack who finds enabling a team to build better software deeply satisfying.
You will shape critical systems, mentor senior and junior developers through complex technical decisions, conduct rigorous code reviews across multiple technology domains, and directly influence the platform's trajectory through strategic engineering leadership.
This is for someone who:
• Engages thoughtfully when a junior developer asks targeted architectural questions—because you see an opportunity to shape how someone thinks about systems
• Takes time to explain subtle type-safety issues in code review, understanding that feedback is a teaching moment
• Can present architecture clearly to executives and confidently explain both what we're building and why it matters
• Finds more energy in the code your team ships than in the code you write individually
• Has proven depth across the full stack and a track record of developing engineers into stronger contributors
If that describes you, we'd like to talk.
Core Responsibilities
1. Technical Architecture & Systems Thinking (40%)
• Shape architectural decisions across the full stack: How should the component layer handle dynamically generated forms? What's the right approach to validate complex cross-field dependencies in the FormBuilder? What separation of concerns makes sense between the Generator Lambda and the Parent Backend?
• Guide architecture discussions: Help senior developers think through design trade-offs. Should we use NgRx or Angular signals for this feature? When does a new Lambda function become worthwhile given cold-start costs?
• Identify and address system-wide bottlenecks: Work across layers to improve performance. Explore Lambda cold-start optimization, RDS query efficiency, and DynamoDB access patterns.
• Establish patterns and guide consistency: Define coding conventions that work across Python, TypeScript, and Terraform. Help new team members understand the reasoning behind architectural choices.
What this looks like in practice: You're able to justify architectural decisions with technical reasoning. When someone questions an approach, you can explain the trade-offs you considered. You can write code in multiple languages to validate an approach if needed.
2. Code Review & Technical Guidance (30%)
• Full-stack PR reviews: Review Python FastAPI endpoints and Angular components with equal depth, understanding how they interact.
• Deep technical review: Catch issues thoughtful code review can surface:
o RxJS Observable lifecycle and potential memory patterns in Angular
o Query efficiency and data loading patterns in SQLAlchemy
o Terraform module organization and state management implications
o Type safety and TypeScript coverage gaps
o AWS security and IAM configurations
• Educational feedback: Your code reviews help the team learn. When you identify an issue, reviewees understand not just what changed, but how to think about similar problems in the future.
• Define quality expectations: Work with the team to establish what \"production-ready\" means for this platform and support consistent application of those standards.
What this requires: Experience reviewing code across teams and multiple languages. You know how to write feedback that resonates—clear, constructive, and focused on helping people improve.
3. Mentorship & Team Development (20%)
• Expand specialist capabilities: Help backend specialists learn to contribute to the forms-engine. Support frontend experts in understanding FastAPI patterns.
• Accelerate junior developers: Pair on complex problems. Explain the reasoning behind patterns like DataState. Connect architectural choices to implementation details and performance implications.
• Identify and address gaps: Recognize when someone is struggling with a technology and provide targeted support—training, pair programming, or guidance through architectural decisions.
• Create growth opportunities: Stretch the team into new areas. A backend engineer working on their first Terraform contribution. A frontend specialist implementing an AWS Lambda authorizer.
What this requires: Genuine investment in people's growth. You've walked developers through major transitions (generalist to specialist, specialist to full-stack, or into new technology areas). You understand that team strength grows when individuals expand their capabilities.
4. Stakeholder Communication & Technical Leadership (10%)
• Explain to diverse audiences: Translate architectural choices and trade-offs for product managers, executives, and business stakeholders. Connect \"optimizing DynamoDB queries\" to \"improving form submission latency by 30%.\"
• Shape technical direction: Contribute the engineering perspective on feasibility, risk, and what unlocks future capabilities.
• Support release confidence: You understand the code changes, comprehend the risks, and know what to monitor. You can stand behind releases.
Required Qualifications
Technical Skills
Frontend (Production Experience)
• 5+ years of Angular (including handling version migrations, optimizing change detection, and guiding teams through reactive patterns)
• Strong TypeScript skills with generics, discriminated unions, and strict mode
• RxJS depth: You understand hot vs. cold observables, unsubscription patterns, and can identify potential memory issues in reviews
• NgRx state management: You've designed stores at scale, optimized selectors, and evaluated architectural implications
• CSS Grid & Responsive Design: You can assess component hierarchy and layout decisions
• Material Design: You've worked within it and know when and how to extend it
Backend (Production Experience)
• 5+ years of Python (async/await, type hints, data modeling)
• FastAPI production experience: session management, dependency injection, middleware
• SQL and ORMs (SQLAlchemy): You write efficient queries and review them critically
• AWS services: Understanding of Lambda behavior, IAM least-privilege patterns, VPC networking
• REST API design: Versioning, error handling, idempotency
• Testing frameworks: pytest, testing st
Job Title: Senior Software Engineer
Reports To: Manager of Application Development
About the Role:
The Senior Software Engineer is a hands-on technical leadership position responsible for designing, building, and maintaining high-quality software solutions. This role emphasizes both individual development work and ownership of design decisions for features and subsystems. Modern tools, including AI-assisted development and architectural support, are leveraged to drive delivery while maintaining accountability for technical outcomes.
Responsibilities:
- Design, implement, test, and maintain scalable, secure, and reliable applications and services.
- Act as a senior technical contributor, with responsibility for the design and implementation of features and subsystems.
- Contribute actively to development tasks, applying advanced coding expertise in several programming languages and frameworks.
- Participate in architectural discussions and support incremental evolution of systems with team leads.
- Conduct code reviews and mentor engineering team members, fostering best practices and ongoing improvement.
- Translate requirements from product owners, business analysts, and stakeholders into technical solutions.
- Identify and mitigate technical risks in assigned systems and projects.
- Support and enhance cloud-based applications (Azure, AWS) with emphasis on performance, reliability, and scalability.
- Collaborate effectively with onshore and offshore teams to ensure successful project execution.
- Keep abreast of industry trends and new technologies to encourage innovation.
- Utilize AI-assisted tools to expedite design, documentation, and implementation, while ensuring technical quality.
- Lead and support AI-related initiatives, drawing on prior experience with AI/ML technologies; recommend and implement suitable AI tools and frameworks.
- Test and demonstrate emerging AI tools and platforms via proofs of concept (POCs) to highlight business value.
- Guide customers in leveraging AI to optimize business processes; support teams working on business-facing AI efforts.
- Collaborate with stakeholders to contribute to defining an AI roadmap aligned with organizational strategy and technology objectives.
Qualifications:
- Bachelor’s degree in Computer Science, Software Engineering, or a related field; Master’s degree preferred.
- A minimum of 5 years in a Senior Software Engineer, Lead Developer, or similar role, with proven success delivering production systems.
Required Skills:
- Strong understanding of software development methodologies (e.g., Agile, DevOps) and architectural frameworks.
- Proficient in programming languages such as C#, Python; excellent problem-solving and critical thinking skills.
- Web Development: Experience with modern front-end frameworks (e.g., React, Vue.js).
- Mobile Development: Knowledge of mobile app development tools (e.g., Cordova, Ionic).
- Cloud Development: Experience managing cloud-hosted applications, including Azure Functions and Event Hubs.
- Database Management: Ability to develop and debug stored procedures, views, and tables in SQL Server and MySQL; basic database administration for data integrity and security.
- API Development: Skilled at designing, building, and debugging APIs; experience with RESTful APIs and tools like POSTMAN and SOAPUI.
- DevOps: Designing branching strategies; implementing and maintaining CI/CD pipelines for test automation and deployment.
- Containerization: Experience with Docker and Kubernetes for application development and deployment.
- Security: Understanding of secure coding and application security best practices.
Preferred Skills:
- Ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Effective teamwork, working with cross-functional groups including developers, project managers, and analysts.
- Strong problem-solving abilities and the capacity to make effective decisions under constraints.
- Leadership through mentoring and influencing technical direction.
- Adaptability to new technologies and changing environments.
- Critical thinking in evaluating options and making informed decisions.
- Effective time management across multiple projects.
- Empathy for team and stakeholder perspectives to foster collaboration.
Qualifications Required A Bachelor's Degree; Graduate Degree preferred At least 3 years of experience with Python Linux / Unix environment experience Experience with PostgreSQL, or other relational databases Able to quickly understand and discuss requirements from Portfolio Managers Preferred Previous experience in low-latency trading environments Familiar with quantitative finance and electronic trading concepts and financial data Equities, futures, FX, or other financial instruments knowledge Experience with containerization and orchestration technologies Experience building and deploying systems that utilize services provided by AWS, GCP or Azure Experience with other programming languages, such as C/C++, Java, Scala, Go, or C# Apache, Confluent Kafka experience Experience automating SDLC pipelines
Job Title: Embedded Validation Engineer
Location: Charlotte, NC
Job Type: Full-Time
Role Overview
We are seeking a technically strong Embedded Validation Engineer to serve as the Controls and Quality Assurance (QA) point of contact for lab validation and sustaining programs. The role focuses on requirements-based validation, disciplined test execution, defect reporting, and traceability across multiple product programs.
The ideal candidate will work closely with Systems Engineering, Product Development, and QA teams to validate embedded control systems, execute lab testing, and improve test automation and validation processes.
Key Responsibilities
Requirements-Based Validation
- Collaborate with Systems Engineering teams to derive validation strategies and test plans from system requirements.
- Develop and maintain requirement-to-test case traceability.
- Ensure validation activities align with product specifications and engineering requirements.
Lab Test Execution
- Serve as the Controls Validation Point of Contact (POC) for lab validation activities.
- Execute validation tests on prototype hardware and embedded control systems.
- Document test procedures and record pass/fail outcomes with technical accuracy.
Documentation & Traceability
- Maintain organized test documentation including test plans, execution logs, and validation reports.
- Ensure traceability between requirements, test cases, and defect reports.
Defect Reporting & Tracking
- Identify, document, and report defects with clear technical descriptions and reproducible steps.
- Collaborate with development teams to analyze root causes and track defect resolution.
Reporting & Quality Reviews
- Prepare concise 2–3 slide technical summaries of test results and validation findings.
- Present validation updates during PRQRB/SQA or departmental review meetings.
Test Bench & HIL Development
- Design and build test bench setups and Hardware-in-the-Loop (HIL) simulators for validation.
- Support legacy platforms and existing validation environments.
Automation Development
- Contribute to Python-based test automation and validation frameworks.
- Identify opportunities to improve test efficiency through automation.
Product Support & Continuous Improvement
- Support new product development, sustaining engineering, and validation process improvements.
- Drive enhancements in test infrastructure, lab workflows, and validation methodologies.
Required Qualifications
- Bachelor’s degree in Controls Engineering, Software Engineering, Electrical Engineering, or related field.
- 5+ years of experience in embedded systems validation, SQA, or controls testing.
- Strong understanding of Software Quality Assurance (SQA) fundamentals, including test execution and documentation.
- Experience validating embedded control systems and equipment controls.
- Hands-on experience with lab-based validation and prototype testing.
- Knowledge of controls inputs/outputs, sensors, and system interfaces.
- Experience with bench wiring, test setup, and instrumentation.
- Strong analytical skills and familiarity with engineering basics such as heat exchangers and unit conversions.
- Experience with Python scripting and test automation.
Title: Python with AI(Only w2)
Location: Atlanta GA(Onsite/Only Locals)
Must have mins 10-12 years of overall years of experience
Must haves.
- Strong Python programming (OOP, typing, async programming).
- Experience with API development (FastAPI or Flask).
- PY-test framework knowledge for unit testing.
- Git hub branching familiarity
- Framework development experience with PyTorch, TensorFlow, Hugging Face Transformers, LangChain, OpenAI API
- Basic Cloud knowledge like server less compute, http traffic, CICD concepts
Nice to Have:
- Deep Learning: Neural networks, CNNs, RNNs, transformers, attention mechanisms.
- Azure: resource groups, container apps, vnet, logging, cosmos db.
- SQL (Query writing) experience like SQL server/Azure SQL/Oracle/PostgreSQL
- API security with AuthN/AuthZ understanding of OpenID or oAuth2 flows
If I missed your call ! Please drop me a mail.
Thank you,
Harish
Talent Acquisition
Astir IT Solutions, Inc - An E-Verified Company
Email:
Direct : 7326946000*788
50 Cragwood Rd. Suite # 219, South Plainfield, NJ 07080