The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

About the Role

The AI Integrations team builds the tools that bring AI into Telnyx's core products — think voice agents, intelligent messaging, and real-time AI features that improve our customer experience. We need a strong fullstack engineer to help us move faster.

This is a mid-level IC role. You'll own features end-to-end: building React interfaces, writing Node.js services, wiring up databases, and shipping things that work. AI experience isn't required — you'll pick that up here. What matters is that you can build solid fullstack products and want to learn.

What You'll Work On

• Fullstack features across our AI product suite — frontend to database
• Integrating LLMs and AI capabilities into real world applications (with support from the team)
• Building interfaces that make complex AI tools feel simple
• Shipping iteratively — we value working software over perfect plans

Tech Stack

Core (you should know this well):
React 18+, TypeScript, Tailwind CSS, Node.js, PostgreSQL, Prisma, TanStack Query, Docker, Kubernetes

Bonus (nice to have, happy to teach):
Next.js 15+, LLM integration, LangChain/LangGraph RAG/Embeddings, Vector Databases, MCP, WebSockets, WebRTC, Radix UI, Shadcn UI, Framer Motion

What We're Looking For

You're genuinely comfortable across the stack — not a frontend dev who can "do backend" or vice versa. You've built and shipped real features. You take ownership, communicate clearly, and don't need hand-holding.

AI interest is a plus, but we'd rather have a strong fullstack engineer who's curious than an "AI enthusiast" who can't ship.

We move fast on modern web tooling (React/Next, TypeScript, Tailwind). Expect frequent upgrades.

Values

• Ownership — you see things through
• Collaboration — you work well with others and communicate proactively
• Adaptability — comfortable with ambiguity and changing requirements
• Growth mindset — eager to learn, takes feedback well


#LI-KG1 #LI-VIETNAM
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems
  
  
  

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: We're seeking a Senior Site Reliability Engineer to join the team. You will build and operate the infrastructure and tooling behind WorldQuant's data ingestion pipelines — systems that onboard, validate, and deliver large-scale datasets to the firm's research platform. This is a 70% build / 30% operate role. You'll spend most of your time engineering automation, observability, and developer tooling, while also participating in on-call rotations and incident response for production data pipelines. You'll partner with engineering, analyst, and research teams to ensure reliability at scale — this requires excellent analytical skills, clear communication, and the ability to collaborate across teams.

What You'll Do:

Build (70%):

• Design and develop automation, monitoring, CI/CD, and reliability features for the data onboarding pipeline
• Develop and maintain internal infrastructure and services that reduce toil and improve pipeline reliability
• Build observability solutions — dashboards, alerting, log aggregation — using Grafana, the ELK stack, and Vector
• Design and implement CI/CD pipelines, test automation, and release management workflowsWrite infrastructure-as-code for provisioning, scaling, and managing platform components: Kubernetes, bare metal hosts
• Integrate and extend tools such as Redis, Celery, MySQL

Operate (30%): Keep production data pipelines healthy and respond to incidents

• Participate in on-call rotation, respond to production incidents, and drive post-mortems
• Define and track SLOs/SLIs for pipeline reliability, latency, and data freshness
• Diagnose platform performance and reliability issues, driving them to root cause
• Create and maintain runbooks for common operational scenarios
• Plan capacity and optimize resource utilization

What You'll Bring

• 8+ years of experience in SRE, DevOps, or platform engineering roles
• Linux expertise: Power user proficiency in Linux with ability to manage infrastructure, deploy services, and troubleshoot production systems
• Python proficiency: Strong scripting and automation skills; experience building CLI tools, API clients, monitoring integrations, and operational tooling in Python
• Kubernetes & containers: Deep hands-on experience with Kubernetes — deploying, scaling, debugging, and managing production workloads. Familiarity with Helm, resource management. Solid experience with Docker
• Observability: Hands-on experience with monitoring stacks — Grafana, Prometheus, ELK (Elasticsearch, Logstash, Kibana), or similar. Experience designing dashboards, alerts, and SLO-based reliability tracking
• CI/CD & infrastructure-as-code: Experience designing and maintaining CI/CD pipelines (GitLab CI, or similar), including test automation and release management. Familiarity with Ansible or similar IaC tools
• Databases: Working knowledge of relational databases (MySQL/PostgreSQL), query tuning, and operational database management
• Message queues & streaming: Experience with Kafka, Redis pub/sub, or Celery for event-driven architectures
• Networking & APIs: Understanding of network fundamentals, DNS, load balancing, and REST/gRPC APIs
• Incident management: Experience with on-call rotations, incident response, post-mortems, and runbook-driven operations
• Leadership & management: Proven track record of leading a team — mentoring engineers, driving technical roadmaps, coordinating cross-team initiatives, and managing priorities. Comfortable owning team delivery and representing the team to stakeholders
• AI-agent readiness: Openness to working alongside AI coding agents and LLM-powered tools as part of the development and operations workflow — treating AI as a force multiplier for automation, incident analysis, and toil reduction
• Nice to Have:
  • Cloud platforms: Exposure to GCP or AWS for compute, storage, and managed services
  • Data tools: Familiarity with Apache Arrow, gRPC, or columnar data formats
  • Big data platforms: Familiarity with Hadoop or Apache Spark for large-scale data processing
  • Programming languages: C/C++, Golang, Scala, JavaScript
  • Financial services or data-intensive industry background
  • SRE culture: Familiarity with Google's SRE book principles — error budgets, toil tracking, blameless post-mortems

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events, Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-QM1

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: As an NLP Data Engineer at WorldQuant, you will be at the heart of transforming unstructured text into actionable, high‑value insights that power quantitative investment strategies. This is a hands-on, engineering role where you’ll design, build, and scale the data pipelines that underpin our data research. This role is ideal for someone who loves building production systems, enjoys working deeply with text and large language models, and wants their engineering work to empower quantitative research at the firm. You’ll join a highly technical, collaborative environment where you work closely with Research and where your ideas can quickly translate into impact at scale.

What You’ll Bring:

• BSc/M.Sc. from a leading university in Computer Science, Engineering, or related discipline
• 5 years of demonstrated experience programming scalable and robust software in Python
• Demonstrated experience building or maintaining data pipelines
• Basic knowledge of probability and statistical theory
• Experience working in Linux environments
• Experience with building and operating ML inference pipelines.
• Experience with using LLM for structured data extraction.
• Strong communication skills; ability to express complex concepts in simple terms
• Experience in the financial services industry is a big plus
• Knowledge of workflow scheduling techniques (e.g. Airflow) is a plus
• Prior experience working with text data in a data science/quantitative project environment

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-QM1

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: We're seeking a senior developer to join our team. You will design, build, and operate large-scale data and ETL systems that power the firm's research and investment workflows. This is a high-autonomy role - you'll own critical systems end-to-end, make architectural decisions, and deliver solutions with minimal guidance. We need someone who is self-directed, able to lead themselves, take ownership of outcomes, and drive complex problems to resolution independently. You should be comfortable communicating across teams, articulating technical trade-offs to stakeholders, and mentoring others through code review and collaboration.

What You'll Do:

• Design, develop, and own backend services and data pipelines that process large volumes of data optimally and at scale
• Architect data storage and processing solutions, including schema design, query optimization, and data modeling
• Build and maintain APIs, messaging systems, and integration layers that connect data producers and consumers
• Drive technical decisions - evaluate trade-offs, choose the right tools, and define system boundaries
• Take ambiguous requirements and break them down into deliverable, well-engineered solutions
• Diagnose and resolve complex production issues - applying strong analytical and systems thinking
• Improve engineering practices: testing, CI/CD, observability, and documentation

What You'll Bring:

• 8+ years of professional software development experience
• Strong programming proficiency: Mastery of at least one major programming language (Python, Java, Go, C++, or equivalent). Beyond syntax fluency, you should understand language internals and be able to apply that depth to write performant, reliable code
• System design: Proven ability to architect distributed, scalable, and fault-tolerant systems. Understanding of common patterns - event-driven architecture, service decomposition, data partitioning, caching strategies
• Data engineering: Experience building ETL/ELT pipelines, working with batch and streaming data, and handling large-scale data processing
• Database proficiency: Deep understanding of relational databases (PostgreSQL, MySQL) and familiarity with analytical/columnar stores; strong SQL skills including query optimization
• Software engineering depth: Strong grasp of data structures, algorithms, design patterns, and software architecture principles - applied in production, not just theory
• API design: Experience designing clean, well-documented REST/gRPC APIs
• Incident response mindset: Ability to diagnose production issues methodically, drive root-cause analysis, and feed into post-mortems and operational improvement
• AI-agent readiness: Openness to working alongside AI coding agents and LLM-powered tools as part of the development workflow - using AI as a force multiplier for code generation, review, debugging, and documentation
• Nice to Have:
  • Python mastery: Advanced knowledge of Python internals, concurrency (asyncio, threading, multiprocessing), performance profiling, packaging, and strong experience with frameworks such as FastAPI/Flask, SQLAlchemy, pytest, and mypy/type annotations
  • Observability and distributed tracing: Experience with monitoring and observability stacks - metrics, structured logging, distributed tracing (OpenTelemetry, Grafana, ELK) - for diagnosing system behavior and bottlenecks in production
  • DevOps practices: Familiarity with containerization (Docker), CI/CD pipelines (GitLab CI, Jenkins), and infrastructure-as-code (Ansible, Terraform)
  • Programming language versatility: Proficiency in additional languages that complement data platform work - C++ for performance-critical systems, Scala for distributed data processing with Apache Spark, or Rust for high-performance data engineering
  • Team leadership and management: Experience leading a development team, running sprints, conducting code reviews, mentoring engineers, and managing stakeholders' expectations
  • Message queues and streaming: Experience with Kafka, Redis, or similar event-driven architectures
  • Data orchestration: Exposure to Airflow or similar workflow orchestration frameworks
  • Frontend / full-stack awareness: Familiarity with modern web technologies (React, TypeScript) for building internal UIs and dashboards
  • Financial services or quantitative finance background
  • Open-source contributions or a public portfolio of technical work

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-QM1

The Role: Research is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our researchers are in constant search of new alphas. Researchers at WorldQuant employ tested processes seeking to identify high-quality predictive signals that we believe are undiscovered by the wider market. These signals are mathematical expressions of data that are used as inputs in our quantitative models. 

WorldQuant is seeking an exceptional individual to join the firm as a Quantitative Research Intern. The person must have a good understanding of the investment research process to create computer-based models that seek to predict movements of global financial markets. This position is responsible for assisting with daily research and analysis tasks – which includes scripting for monitoring and alpha signal analysis. Candidates need not have prior knowledge of financial markets, but must have a strong interest in learning about stock markets and other capital markets. Successful candidates will self-starters, have a research scientist mind-set, and be creative and persevering deep thinkers who are motivated by unsolved challenges. Our highly accomplished senior staff will provide the interns with mentoring and guidance to help them succeed.

What You’ll Bring:

• Candidates holding or pursuing a BS (Hons), MS or PhD in Computer Science, Artificial Intelligence, Computer Vision, Machine Learning, Data Science or Mathematics are strongly preferred
• Exceptional candidates without an advanced degree will also be considered. Prior quant analysis or trading experience is a benefit.
• Programming skills is a must (Python/ C++/Java)
• Have deep learning, LLM, NLP or prompt engineering course work or experience is a plus
• Participated in national and international mathematics or programming competitions (preferred)

What We Offer:

• 6-month learning and development path – challenge your intellectual mind
• Competitive compensation package with clear career road-map – opportunities to transition to a full-time role
• Online Medical support
• Team building activities every month – employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Happy-hour with tea break, snacks and meals every day!

#LI-NV1

What You'll Do:

• Architect As-A-Service solutions based on Open Source Software.
• Work within the team on the various products that the team supports.
• Develop tools to improve our ability to rapidly deploy and effectively monitor services in a large-scale distributed environment.
• Work with teams to design, develop, and implement innovative software solutions related to the DevOps and Agile transformation of the enterprise.
• Participate in periodic on-call duties.
• Collaborate with peers both inside and outside your team.

What You’ll Bring:

• Solid understanding and experience working with Linux based systems.
• Proficiency in Python for building APIs, developing automation scripts, and creating operational tools.
• Experience with modern authentication and authorization protocols such as OIDC, SAML, and Kerberos to ensure secure access to our platforms.
• Strong working knowledge of container orchestration with Kubernetes (K8s) is highly preferred. Experience with other cluster management systems like Slurm is a plus, especially if you have a background in large-scale computational environments.
• Proven experience with Infrastructure as Code (IaC) to automate the provisioning and management of our infrastructure, using tools like Terraform, Ansible, and Helm.
• Hands-on knowledge with containerization systems such as Docker or Podman.
• Experience with CI/CD, GitLab (preferred), GitHub or Git.
• Experience with agile development.
• A strong background in observability, with experience in monitoring and logging using tools like Prometheus, Grafana, and the OpenTelemetry (OTEL) stack.
• Experience using AI/LLM-powered tools and its concepts (MCPs, A2A,…) to support your development workflow is a plus.
• A great team attitude (our job is to make life easier for other teams!).
• Strong written and verbal communication skills in English.

What We Offer:

• Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday
• We offer a strong culture of learning and development: training courses, library, speakers, share and learn events
• Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people
• Premium Health Insurance and Employee Assistance Program
• Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family
• Team building activities every month: Local engagement events – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc.
• Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams
• Happy-hour with tea break, snacks and meals every day in the office!

#LI-QM1