Senior Software Engineer, AI Platform and Enablement Job at Descript (San Francisco)

Senior Software Engineer - Studio - Java, AI

As a Senior Software Engineer, you’ll build the backend that powers AI features ...

Location

United States , New York

Salary:

175000.00 - 240000.00 USD / Year

Clear Street

Expiration Date

Until further notice

Requirements

At least 7+ years of strong proficiency in enterprise Java
Experience designing and deploying AI/ML or LLM-backed systems in production
Familiarity with LLM tooling and patterns: (e.g. tool calling, RAG pipelines and knowledge bases, evals, cost/latency tradeoffs, basic red-teaming)
Experience in supporting and running systems in a production environment
Comfortable working in a dynamic environment, partnering with cross-functional teams, and moving from prototype to reliable production

Job Responsibility

Design, implement, and productionize reliable AI workflows to augment the Studio trading platform
Build tooling to monitor, tune, and evaluate models and workflows, as well as applicable guardrails to ensure outputs meet quality and regulatory requirements
Collaborate with technical and non-technical teams across the firm to identify high ROI AI opportunities
Build rapid prototypes and translate them into production-grade systems. Utilize the latest AI-powered development tools to iterate quickly
Create reusable libraries, SDKs and tooling to enable AI development throughout the firm
Stay current on the latest in applied AI. Read papers, evaluate new models, test out new tools
Participate in code review and architecture design, manage deployments, and support and contribute to the success of the overall Studio platform

What we offer

Competitive compensation, benefits, and perks
Company equity
401k matching
Gender neutral parental leave
Full medical, dental and vision insurance
Lunch stipends
Fully stocked kitchens
Happy hours

Fulltime

Sr. Technical AI Enablement Engineer

ModelOp is seeking a highly skilled Sr Technical AI Enablement Engineer to join ...

Location

United States , Utah, Chicago

Salary:

Not provided

ModelOp

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a related field
10+ years of experience in technology-based consulting, technical enablement, or related roles
Experience in custom software delivery and complex system troubleshooting
Exceptional presentation skills for all audiences: from senior business executives to data scientists, architects, and governance teams
Proven ability to translate loose AI governance requirements into actionable implementation details across multiple workstreams
Experience with AI tools, platforms, and model development processes, along with a solid understanding of how governance and compliance mechanisms apply at each stage of the AI model lifecycle
Familiarity with AI regulations/guidelines (e.g. EU AI Act, OSFI E-23, NIST AI-RMF), ideally in specific verticals (e.g. SEC/OCC, FDA)
Strong experience in working with technical teams to embed governance processes into an existing model lifecycle

Job Responsibility

Implementation Planning: Lead customers in planning the implementation of ModelOp within the customer’s existing AI program
Technical Troubleshooting: When customer issues are raised, take lead on triaging the issue, and work with the customer technical team to obtain information (logs, etc.), conduct initial troubleshooting, and identify the next course of action
Process Design: Collaborate with customer teams to translate the customer’s AI governance policies and procedures into actionable and automated workflows within ModelOp, whilst simultaneously advising on best practices from other customers and experience
Inventory & Reporting Configuration: lead customers in designing the appropriate customizations for the metadata structure, use case forms, and dashboards within ModelOp to align with their inventory and reporting requirements
Testing & Monitoring Enablement: lead customer sessions in identifying and configuring the right set of tests and monitors for their specific AI use cases / models
Customer Enablement: Work closely with the customer to drive consumption of ModelOp software, by onboarding new AI use cases in the platform
Training & Support: Lead customer workshops, training sessions, and knowledge transfer activities to ensure customer teams understand and can effectively use ModelOp for their daily AI governance work
Documentation: Document processes, configurations, and troubleshooting steps for both technical and non-technical audiences
Learning: Stay updated on the latest developments in AI governance and related technologies to guide customers and inform product enhancements

What we offer

ModelOp offers full benefits, including a retirement package and comprehensive health insurance

Fulltime

Senior AI Engineer

We are seeking a Senior AI Engineer (L4, Individual Contributor) to design, buil...

Location

India , Chennai

Salary:

Not provided

Arcadia

Expiration Date

Until further notice

Requirements

12+ years of professional software engineering experience
3+ years in AI/ML development
Strong expertise in Python, PyTorch/TensorFlow, scikit-learn, and ML tooling (MLflow, LangChain)
Proficiency with SQL, cloud services (AWS), containers (Docker, Kubernetes), and distributed systems
Understanding of modern AI research (LLMs, diffusion models, transformers)
Experience deploying ML models in production with CI/CD
Strong analytical skills, ability to balance speed and rigor in experimentation
A passion for sustainability and the clean-energy mission
Experienced with building agentic pipelines with the latest models from Anthropic, Google, OpenAI, and more

Job Responsibility

Integrate with LLMs and be an expert in prompt engineering to derive the right results from the models with limited hallucination
Design and train ML/AI models (forecasting, NLP, graph learning, generative AI) to improve data quality, cost effectiveness, and system scalability
Deploy and optimize models for large-scale production workloads using Python-based services in AWS/Kubernetes environments
Build robust, automated data pipelines and ML Ops workflows for continuous training and deployment
Research and experiment with modern AI methods (transformers, foundation models, reinforcement learning) and adapt them to energy-sector challenges not limited to utility statements
Drive performance improvements in model accuracy, latency, and cost efficiency
Collaborate with Product, SRE, and Analytics teams to deliver AI-enabled features across Arcadia’s platform
Write clean, maintainable code, contribute to architecture reviews, and mentor junior engineers
Build true agentic workflows with multi-step processing incorporating RAG pipelines and MCPs

What we offer

Competitive compensation and employee stock options
Hybrid/remote-first working model (India-based role, with global collaboration)
Flexible leave policy
Comprehensive medical insurance (self + family members)
Annual performance cycle + quarterly recognition awards
A supportive, diverse engineering culture grounded in empathy, teamwork, and innovation

Fulltime

Senior ML Platform Engineer

At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP e...

Location

United States , Boston

Salary:

150000.00 - 210000.00 USD / Year

Whoop

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s Degree in Computer Science, Engineering, or a related field
or equivalent practical experience
5+ years of experience in software engineering with a focus on ML infrastructure, cloud platforms, or MLOps
Strong programming skills in Python, with experience in building distributed systems and REST/gRPC APIs
Deep knowledge of cloud-native services and infrastructure-as-code (e.g., AWS CDK, Terraform, CloudFormation)
Hands-on experience with model deployment platforms such as AWS SageMaker, Vertex AI, or Kubernetes-based serving stacks
Proficiency in ML lifecycle tools (MLflow, Weights & Biases, BentoML) and containerization strategies (Docker, Kubernetes)
Understanding of data engineering and ingestion pipelines, with ability to interface with data lakes, feature stores, and streaming systems
Proven ability to work cross-functionally with Data Science, Data Platform, and Software Engineering teams, influencing decisions and driving alignment
Passion for AI and automation to solve real-world problems and improve operational workflows

Job Responsibility

Architect, build, own, and operate scalable ML infrastructure in cloud environments (e.g., AWS), optimizing for speed, observability, cost, and reproducibility
Create, support, and maintain core MLOps infrastructure (e.g., MLflow, feature store, experiment tracking, model registry), ensuring reliability, scalability, and long-term sustainability
Develop, evolve, and operate MLOps platforms and frameworks that standardize model deployment, versioning, drift detection, and lifecycle management at scale
Implement and continuously maintain end-to-end CI/CD pipelines for ML models using orchestration tools (e.g., Prefect, Airflow, Argo Workflows), ensuring robust testing, reproducibility, and traceability
Partner closely with Data Science, Sensor Intelligence, and Data Platform teams to operationalize and support model development, deployment, and monitoring workflows
Build, manage, and maintain both real-time and batch inference infrastructure, supporting diverse use cases from physiological analytics to personalized feedback loops for WHOOP members
Design, implement, and own automated observability tooling (e.g., for model latency, data drift, accuracy degradation), integrating metrics, logging, and alerting with existing platforms
Leverage AI-powered tools and automation to reduce operational overhead, enhance developer productivity, and accelerate model release cycles
Contribute to and maintain internal platform documentation, SDKs, and training materials, enabling self-service capabilities for model deployment and experimentation
Continuously evaluate and integrate emerging technologies and deployment strategies, influencing WHOOP’s roadmap for AI-driven platform efficiency, reliability, and scale

What we offer

equity
benefits

Fulltime

Senior Software Engineer, Prenatal

Ready to redefine what's possible in molecular diagnostics? Join a team of brill...

Location

United States , Menlo Park

Salary:

190081.00 - 211201.00 USD / Year

BillionToOne

Expiration Date

Until further notice

Requirements

5 - 7 years of professional software development experience with a proven track record of delivering complex projects adhering to best practices
Deep understanding and experience using web frameworks like Django and FastAPI
Strong system design and architecture capabilities, applying domain-driven design to translate complex business domains into clear, scalable service and data boundaries.
Familiarity with modern AI-driven development practices and tools.
Strong foundation in cloud services, preferably AWS, including ECS, S3, AWS Batch, EC2, and AWS Lambda, enabling effective architecture and management of complex systems
Excellent communication and collaboration skills, with the ability to work effectively in a team-oriented environment
Excited about working in-person with our team in Menlo Park

Job Responsibility

Design, build, and operate scalable, high availability backend services, APIs, and data integrations that power customer facing product experiences
Lead technical delivery across the full lifecycle: architecture, design, implementation, testing, deployment, and ongoing operations
Collaborate closely with product, design, and cross functional engineering teams to deliver performant, reliable, and intuitive platform capabilities
Develop clean abstractions and platform APIs that simplify complex LIS workflows while balancing developer velocity with long term system stability
Build and maintain secure, reliable cloud infrastructure on AWS, including compute environments, networking, container orchestration, storage, and environment automation
Implement CI/CD pipelines, Infrastructure as Code, configuration management, and automated environment provisioning to standardize and accelerate delivery
Embed observability and operational excellence into the platform by default through robust monitoring, logging, alerting, and reliability patterns
Ensure the scalability, maintainability, and overall health of backend and cloud systems as the platform grows to support large enterprise workloads and future global expansion
Foster a culture of ownership, technical excellence, learning, and continuous improvement within the engineering team
Apply AI-assisted tooling and workflows to improve developer productivity, automate routine engineering tasks, enhance code quality, and accelerate troubleshooting

What we offer

Working alongside brilliant, kind, passionate and dedicated colleagues, in an empowering environment, toward a global vision, striving for a future in which transformative molecular diagnostics can help millions of patients
Open, transparent culture that includes weekly Town Hall meetings
The ability to indirectly or directly change the lives of hundreds of thousands patients
Multiple medical benefit options
employee premiums paid 100% of select plans, dependents covered up to 80%
Extremely generous Family Bonding Leave for new parents (16 weeks, paid at 100%)
Supplemental fertility benefits coverage
Retirement savings program including a 4% Company match
Increase paid time off with increased tenure
Latest and greatest hardware (laptop, lab equipment, facilities)

Fulltime

Senior Staff Machine Learning Engineer

Help design our AI platform and develop our next generation of machine learning ...

Location

United States , San Francisco

Salary:

216500.00 - 324500.00 USD / Year

GoFundMe

Expiration Date

Until further notice

Requirements

9+ years of hands-on experience in machine learning engineering, AI development, software engineering, or related fields
Experience emphasizing secure, large-scale, distributed system design, AI/ML pipeline development, and implementation
Extensive experience designing, developing, and operating scalable backend systems
Experience applying software engineering best practices such as domain-driven design, event-driven architectures, and microservices
Deep expertise in agentic workflows, AI evaluation solutions, prompt management, and secure AI development and testing practices
Strong knowledge of relational and document-based databases, data storage paradigms, and efficient RESTful API design
Experience establishing robust CI/CD pipelines, automated testing (unit and integration), and deployment practices
Strong leadership skills, including effective planning and management of complex projects, mentoring of team members, and fostering a collaborative, high-performing engineering culture
Excellent communicator, able to articulate complex technical concepts clearly to both technical and non-technical stakeholders
Bachelor's degree in Computer Science, Software Engineering, or a related technical field (preferred)

Job Responsibility

Design and implement AI platforms to enable scalable and secure access to LLMs from multiple model providers for diverse use cases
Design and implement agentic workflows, agentic tool ecosystems, and LLM prompt management solutions
Design, build, and optimize scalable model training, fine tuning, and inference pipelines, ensuring robust integration with production systems
Influence technical strategy and approach to developing embedding stores, vector databases, and other reusable assets
Lead initiatives to streamline ML and AI workflows, improve operational efficiency, and establish standardized procedures to achieve consistent, high-quality results across our AI systems
Design and develop backend services and RESTful APIs using Python and FastAPI, integrating seamlessly with ML pipelines and services
Take operational responsibility for team-owned services, including performance monitoring, optimization, troubleshooting, and participation in an on-call rotation
Collaborate with both technical and non-technical colleagues, including data and applied scientists, software engineers, product managers, and business stakeholders, to deliver reliable and scalable ML-driven products
Coach and mentor fellow ML engineers, promoting a culture of collaboration, continuous improvement, and engineering excellence within the team
Employ a diverse set of tools and platforms including Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, Coralogix, and GitHub to build, deploy, and maintain scalable, highly available machine learning infrastructure

What we offer

Competitive pay
Comprehensive healthcare benefits
Financial assistance for things like hybrid work, family planning
Generous parental leave
Flexible time-off policies
Mental health and wellness resources
Learning, development, and recognition programs

Fulltime

Senior Engineering Manager, Search Infrastructure

The Search Platform team is responsible for powering all of Rovo Search as well ...

Location

India , Bengaluru

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

4+ years of experience managing high performing, software engineering teams running core services at scale
Deep technical experience building and scaling search applications and distributed systems using large amounts of data on cloud platforms, preferably AWS
Expert level knowledge and understanding of low-latency distributed data management and query processing systems including Lucene based stacks will be strongly preferred
Proven track record of consistent execution delivering outsized results with strong operational rigour
ability to continuously simplify and evolve reliable processes for the team
Strong organisation and communication skills with the ability to drive clarity in an ambiguous environment
effectively communicate technical concepts and results clearly and concisely, and solicit feedback from various stakeholders
Ability to hire, onboard, and retain top talent for your team and foster a culture of innovation, collaboration, and excellence
Passion for mentoring and coaching your team members on best practices, code quality, design patterns, testing and operational skills
Focus on business outcomes and the 80/20 rule

Job Responsibility

Designing the right goals in collaboration
executing and delivering them for our customers
Responsible for building the highest performing teams consisting of deeply skilled and highly motivated engineers
Empowering and enabling team members to exceed their own potential
Primary architect of the culture in your team, aligned with our core values, focused on innovation and excellence
Help hire, develop and work closely with senior engineers to actively drive technical solutions and architecture
Own the quality of decision making along with their long-term outcomes
Continuously upgrading deep technical skills, engineering judgment and strong operational rigour

What we offer

Health coverage
Paid volunteer days
Wellness resources

Fulltime

Senior Agentic AI Developer

Senior Agentic AI Developer to build production-grade autonomous agents and orch...

Location

United States , San Francisco

Salary:

156000.00 - 234000.00 USD / Year

GoFundMe

Expiration Date

Until further notice

Requirements

6+ years in software engineering, with 3+ years hands-on building production-grade AI/ML systems
Deep expertise in LLM agent frameworks (LangGraph, Google ADK, CrewAI, AutoGen, Pydantic AI, LangChain)
Proven ability to architect agentic systems from scratch, including planning/reasoning flows and multi-agent orchestration
Strong Python/TypeScript skills and experience in microservices and distributed infrastructure
Familiarity with vector databases (e.g., Pinecone, ChromaDB), knowledge graphs (Neo4j, Graphiti), and RAG pipelines
Deep autonomous agent architecture knowledge including advanced reasoning, planning, task decomposition, multi-step automation, tool-use patterns, evaluation systems beyond simple response generation
Enterprise integration expertise with RESTful APIs, A2A interoperability, webhook systems, Model Context Protocol (MCP) tools for dynamic tool discovery
Production experience with cloud-native infrastructure (Docker, Kubernetes, AWS/GCP)
Demonstrated experience with reinforcement learning, agent optimization, and agent evaluation techniques
Strong understanding of agent safety, bias mitigation, transparency, and ethical design practices

Job Responsibility

Design and implement LLM-based autonomous agents that perform beyond simple responses — including planning, reasoning, tool-use, and long-term task decomposition
Engineer context- and memory-rich agents that integrate structured data, external APIs, and conversational context to optimize outcomes
Build production-scale orchestration frameworks using tools such as LangGraph, Pydantic AI, Google ADK, and CrewAI to orchestrate complex workflows across campaign creation, optimization, and tracking in distributed microservices architectures
Implement agent-to-agent (A2A) communication protocols using Model Context Protocol (MCP), enabling tool discovery and dynamic peer -to-peer task delegation between specialized agents in our fundraising ecosystem
Develop microservice-based, cloud-native infrastructure for autonomous agent deployment with Docker/Kubernetes, observability tooling, and cloud platforms (AWS/GCP)
Ensure enterprise-grade performance, monitoring, and fault tolerance in agent systems supporting large-scale fundraising workflows
Design sophisticated prompt strategies, agent memory architectures, vector and graph database implementations for maintaining context across multi-turn conversations and long-running campaign lifecycles
Architect and optimize vector and graph database integrations (e.g., Pinecone, Weaviate, ChromaDB) for agent memory and semantic recall
Build custom agentic frameworks for use cases across campaign storytelling, optimization, and donor engagement
Architect frameworks from scratch tailored to fundraising domain challenges, incorporating advanced tool-use capabilities that integrate with platform APIs, knowledge graphs, and external systems

What we offer

Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year
Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere
Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together
Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits
Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being
Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow
Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups
Community Engagement: Make a difference through our volunteering program

Fulltime

Senior Software Engineer, AI Platform and Enablement

Descript

Location:
United States , San Francisco

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
January 09, 2026

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