Senior Software Engineer, AI Data Systems & Database Infrastructure

Ambient.ai; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

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Job summary

Ambient.ai seeks a Senior Platform Engineer to design, build, and scale the database platform powering our AI systems. You will work at the intersection of databases, distributed systems, and AI infrastructure to scale relational, analytical, and vector stores and optimize latency, availability, and operational simplicity.

You will collaborate with AI and engineering teams, implement partitioning, sharding, and caching strategies, and help evolve our data platform while operating under

Qualifications

• 7+ years building and operating production database infrastructure.
• Experience with distributed systems and high-availability.
• Strong knowledge of partitioning, sharding, replication, and indexing.

Responsibilities

• Design, build, and operate scalable database infrastructure for mission-critical production and AI systems.
• Scale relational, analytical, and vector data stores to support product, customer, and AI workloads.
• Improve database performance across latency, throughput, availability, reliability, durability, and cost.
• Own database architecture decisions around partitioning, sharding, replication, indexing, caching, query optimization, and data modeling.
• Operate tier-0 data services with strong reliability, observability, incident response, and disaster recovery practices.
• Build automation and tooling to improve database provisioning, migrations, monitoring, backups, failover, and capacity planning.
• Partner with AI teams to support data infrastructure needs for embeddings, vector search, retrieval workflows, training data, model evaluation, and analytics.
• Build low-latency data-serving patterns that power AI features in production.
• Work closely with engineering teams to design data access patterns that are scalable, reliable, and performant.
• Identify bottlenecks in production systems and drive improvements across application, database, cache, and infrastructure layers.
• Define and enforce best practices for schema design, database usage, data lifecycle management, and operational safety.
• Help evolve our long-term data platform strategy as the company scales.

Skills

PostgreSQL

MySQL

CockroachDB

Vitess

ClickHouse

Vector databases

Redis caching

Python

Go

C++

Kubernetes

Terraform

CI/CD

APIs

Tools

OpenSearch

Milvus

Pgvector

Pinecone

Job description

Build a safer world with us, one incident at a time.

Ambient.ai is the category creator and leader in Agentic Physical Security. Powered by Ambient Pulsar, our first reasoning Vision‑Language Model purpose‑built for physical security, the platform seamlessly integrates with existing security cameras and access control systems to unify monitoring, access control, threat assessment, response, and investigations through an always‑on reasoning layer that augments operators with superhuman capabilities. The results: 95% fewer false alarms, investigations 20× faster, and 10× faster response.

The momentum speaks for itself: we doubled new ARR in FY26 and have delivered results for world‑class customers including Cisco, ServiceNow, SentinelOne, TikTok, Bayer, and MoMA. We recently ranked #71 out of 500 on the Forbes best‑startup employers list.

Founded in 2017 and backed by Andreessen Horowitz, Y Combinator, and Allegion Ventures, Ambient.ai is on a fast‑paced journey to fulfill our mission: prevent every security incident possible.

About The Role

We are looking for a Senior Platform Engineer to design, build, and scale the database platform that powers our most critical production and AI systems. The ideal candidate deeply understands databases and distributed systems, and can build the platforms, abstractions, and scaling patterns required to operate data stores reliably at high scale.

In this role, you will work at the intersection of databases, distributed systems, application architecture, and AI infrastructure. You will help scale relational, analytical, and vector data stores across both the database layer and the application layer. This includes designing systems for partitioning, sharding, routing, caching, replication, query optimization, and high‑availability operations.

You will also work closely with AI teams to build the data infrastructure that supports modern AI applications, including vector search, retrieval‑augmented generation, embedding stores, model evaluation datasets, analytical workloads, and low‑latency data access for AI‑powered product experiences.

The ideal candidate has built or operated database platforms at scale and understands the trade‑offs behind systems like Vitess, CockroachDB, Spanner, DynamoDB, Cassandra, Redis, ClickHouse, and modern vector search systems. You should be comfortable reasoning about latency, availability, durability, consistency, reliability, and operational complexity in Tier‑0 production environments.

This role is ideal for someone who wants to apply deep database and distributed systems expertise to the next generation of AI‑powered products.

What You'll Do

• Design, build, and operate scalable database infrastructure for mission‑critical production and AI systems.
• Scale relational, analytical, and vector data stores to support growing product, customer, and AI workloads.
• Improve database performance across latency, throughput, availability, reliability, durability, and cost.
• Own database architecture decisions around partitioning, sharding, replication, indexing, caching, query optimization, and data modeling.
• Operate tier‑0 data services with strong reliability, observability, incident response, and disaster recovery practices.
• Build automation and tooling to improve database provisioning, migrations, monitoring, backups, failover, and capacity planning.
• Partner with AI teams to support data infrastructure needs for embeddings, vector search, retrieval workflows, training data, model evaluation, and analytics.
• Build low‑latency data‑serving patterns that power AI features in production.
• Work closely with engineering teams to design data access patterns that are scalable, reliable, and performant.
• Identify bottlenecks in production systems and drive improvements across application, database, cache, and infrastructure layers.
• Define and enforce best practices for schema design, database usage, data lifecycle management, and operational safety.
• Help evolve our long‑term data platform strategy as the company scales.

What You'll Bring

• 7+ years of industry experience in database infrastructure, backend infrastructure, distributed systems, or production platform engineering.
• Deep hands‑on experience operating and scaling production databases in high‑availability environments.
• Strong experience with relational databases such as PostgreSQL, MySQL, Aurora, CockroachDB, Vitess, or similar systems.
• Experience with analytical data stores such as ClickHouse, BigQuery, Snowflake, Redshift, Druid, Pinot, or similar technologies.
• Experience with vector databases or vector search systems such as pgvector, Pinecone, Milvus, OpenSearch, or similar systems.
• Strong understanding of partitioning, sharding, replication, indexing, caching, query planning, and storage engine trade‑offs.
• Proven ability to optimize systems for low latency, high availability, reliability, and operational simplicity.
• Experience operating tier‑0 or business‑critical infrastructure services with strong uptime and reliability requirements.
• Strong understanding of caching strategies using systems such as Redis, Memcached, CDN‑backed caches, or application‑level caching.
• Experience with observability, monitoring, alerting, SLOs, capacity planning, and incident response for database systems.
• Strong programming skills, ideally in Python, C++, Go, or similar languages.
• Experience with cloud infrastructure, Kubernetes, Terraform, CI/CD, and infrastructure‑as‑code practices.
• Ability to collaborate effectively with backend, AI, product, security, and infrastructure teams.
• Strong ownership mindset and ability to make pragmatic trade‑offs in complex production environments.

Nice to Have

• Experience scaling databases for real‑time, high‑volume, customer‑facing products.
• Experience with multi‑region database architectures, replication, failover, disaster recovery, and data residency considerations.
• Experience with database migration strategies, online schema changes, zero‑downtime migrations, and backfills.
• Experience supporting AI or ML workloads, including vector search, retrieval‑augmented generation, embedding pipelines, feature stores, training data pipelines, or model evaluation systems.
• Experience with streaming systems such as Kafka, Flink, or Spark.
• Experience with database internals, storage engines, distributed consensus, or query execution.
• Experience managing cost and performance trade‑offs across cloud‑managed and self‑hosted database systems.
• Experience building internal database platforms, tooling, or paved paths for engineering teams.

What Success Looks Like

You will be successful if you can operate critical database systems with a high bar for reliability while continuously improving scale, performance, and developer velocity.

You should have a strong bias for operational excellence, a deep understanding of database trade‑offs, and a proven track record of scaling real production systems. You should be comfortable debugging complex latency issues, planning capacity before it becomes a problem, and designing systems that remain reliable as data volume, query complexity, and customer usage grow.

This role is ideal for someone who has done this work before: scaling production data stores, improving reliability, reducing latency, and supporting teams that depend on data infrastructure as the foundation for their products and AI systems.

Why Join Us

• We are creating an entirely new category within a 180+ billion‑dollar physical security industry and are passionate about our mission to prevent every security incident possible.
• We partner with an incredible customer roster of Fortune 500 companies, including Adobe, TikTok, Gap, and SentinelOne.
• Regular full‑time employees receive stock options to share ownership in the company’s success.
• Comprehensive health and welfare package (Medical, Dental, Vision, Life, EAP, Legal Services, 401k plan).
• Flexible time off to rest and recharge, including a winter break between Christmas and New Year’s for most roles, depending on customer demand.
• The latest tech and awesome swag will be delivered to your door.
• Enjoy a full range of opportunities to connect with amazing co‑workers in a collaborative environment.
• We love hiking, are foodies, and love music.

We’ve found that in‑person time meaningfully supports collaboration, creativity, and team alignment. Our talent, engineering, product, design, and marketing teams work from our Redwood City office three days a week. All other Bay Area employees join on Fridays to stay connected and close out the week together.

Ambient.ai is proud to be an Equal Opportunity Employer. Ambient does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. Ambient is an E‑Verify participant.