Data Pro

Engagement: Contract (Immediate start)
Duration: 2–4 weeks (extension likely)

Role Overview

We are seeking an experienced WebGL / Three.js developer to modernize and enhance a legacy 3D visualization into a high-quality, investor-ready demo. The work focuses on performance, visual polish, and modern Three.js architecture.

Responsibilities

• Upgrade and refactor legacy Three.js code to modern standards
• Build and optimize 3D particle systems and scene interactions
• Implement lighting, post-processing (bloom, depth of field), and camera controls
• Optimize performance for large 4K displays

• Collaborate with product and design on a polished demo experience

   

Required Skills

• Strong experience with Three.js / WebGL
• Modern JavaScript (ES6+); TypeScript preferred
• Experience optimizing real-time 3D scenes (60fps target)

• Solid understanding of cameras, lighting, and post-processing

   

Preferred

• React + Three.js (react-three-fiber)
• Shader/GLSL experience
• Vite or modern build tools

About the Role

We are seeking a Senior Automated QA Engineer who can own quality end-to-end in a fast-moving product environment. This role is highly hands-on and ideal for someone who has built QA processes from scratch, scaled automation, and partnered closely with Product and Engineering to ship reliable software at speed.

You will lead test automation efforts using Playwright, drive API and database testing for microservices, and embed quality deeply into CI/CD pipelines across web and mobile platforms.

Key Responsibilities

• Design, implement, and maintain E2E automated test frameworks (Playwright preferred)
• Own quality strategy across web, mobile (iOS/Android), and API layers
• Perform API-first testing for microservices using Postman and SQL validation
• Integrate automated tests into CI/CD pipelines and enforce quality gates
• Execute and optimize regression, smoke, and release validation testing
• Collaborate with Product, Engineering, and Design in Agile/Scrum ceremonies
• Analyze defects, perform root cause analysis, and reduce production leakage
• Support performance and load testing (k6, JMeter) when needed
• Contribute to tooling decisions, test coverage strategy, and QA best practices
• Participate in AI-assisted testing initiatives and modern QA experimentation
  
   

Required Qualifications

• 6+ years of experience in QA Automation / Software Testing
• Strong hands-on experience with Playwright (or Selenium with migration experience)
• Proficiency in JavaScript / TypeScript (Java acceptable)
• Solid experience testing REST APIs and backend services
• Strong SQL skills (MySQL, PostgreSQL, MS SQL) for data validation
• Experience working with CI/CD pipelines (GitLab CI, Azure DevOps, Git)
• Proven ability to test React / React Native applications
• Deep understanding of SDLC, Agile, and risk-based testing
• Experience testing across web, iOS, Android, and macOS
  
   

Nice to Have

• Experience with visual testing and large-scale content validation
• Familiarity with AI-driven features and AI quality considerations
• Experience with BrowserStack, Expo, Xcode, Android Studio
• Performance testing experience with k6 or JMeter
• Previous experience building QA processes from zero
  
   

Tools & Tech Stack

• Automation: Playwright, Selenium
• API & Performance: Postman, k6, JMeter
• Test Management: TestRail, Zephyr
• Tracking & Delivery: Jira, ClickUp
• CI/CD & VCS: Git, GitLab CI/CD, Azure DevOps
• Databases: MySQL, PostgreSQL, MS SQL
• Platforms: Web, iOS, Android, macOS
• Cloud: AWS, Azure

Senior Python / AI Engineer

Role Overview

We are looking for a Senior Python/AI Engineer with strong experience in machine learning, data engineering, cloud-based architectures, and AI agent pipelines.

You will work directly with the system architect to design and build:

• AI-powered data pipelines,
• prediction and scoring models,
• market-resolution oracles,
• agentic processing pipelines (AWS Bedrock / LangChain / custom),
• high-performance AWS-backed microservices and event-driven workflows.

This role is suited for a self-driven engineer who can operate in a fast-moving architecture.

Key Responsibilities

AI / ML

• Develop and train ML models for market signals, behavioral patterns, user risk segmentation, anomaly detection.
• Implement embedding pipelines, vector search and semantic analysis using:
  AWS Bedrock (Titan, Claude), SageMaker, LangChain, FAISS, OpenSearch, or local pipelines.
• Build LLM-based agents using LangGraph, LangChain, AWS Bedrock Agents, or custom orchestration.
• Work with HuggingFace, PyTorch, scikit-learn, Transformers, Nomic embeddings, etc.

Python Engineering

• Design clean, modular services for data collection, processing, analytics and agentic workflows.
• Build real-time pipelines using:
  asyncio, WebSockets, FastAPI, Redis Streams, Kafka, Celery, Apache Beam (optional).
• Implement microservices interacting with internal APIs, AWS services and data layers.
• Write production-quality Python (3.10+) with Pydantic, SQLAlchemy, Poetry/pipenv, type checking (mypy), and tests (pytest).

Data Engineering

• Create ETL/ELT pipelines aggregating both on-chain and off-chain datasets using:
  AWS Glue, AWS Lambda, Step Functions, Athena, S3, DynamoDB Streams, Kinesis.
• Optimize storage and data access: PostgreSQL, DynamoDB, Redis, S3, OpenSearch.
• Implement observability and monitoring: CloudWatch Logs, Metrics, X-Ray, OpenTelemetry.

DevOps / Cloud (nice to have)

• Experience with AWS:
  • Lambda (Python runtime)
  • ECS Fargate
  • Bedrock (LLMs, embeddings, agents)
  • SageMaker (model training & deployment)
  • SQS, SNS, EventBridge
  • API Gateway
  • OpenSearch
  • Neptune (graph DB)
  • KMS, IAM best practices
• Build and monitor ML services in production using:
  SageMaker endpoints, CI/CD, Docker, Terraform, GitLab CI.

Requirements

Must-Have

• 5+ years of Python engineering experience.
• Strong background in AI/ML, especially NLP and agent-based architectures.
• Experience with LLMs, embeddings, RAG, and vector DBs (FAISS, OpenSearch, Pinecone).
• Strong understanding of async Python and distributed systems.
• Experience with data pipelines (ETL/ELT), real-time event-driven processing.
• Ability to work independently and architect solutions end-to-end.
• Familiarity with AWS cloud services (at least S3, Lambda, API Gateway, CloudWatch).

Nice-to-Have

• Experience with blockchain (EVM, Polygon, oracles).
• Experience with AWS SageMaker training pipelines.
• Understanding of smart-contract-driven workflows.
• Experience with graph analytics: Neo4j, AWS Neptune, RDF/Gremlin.
• Basic Solidity understanding.
• Experience with agent frameworks such as LangGraph.