AI Engineer

Salary: $115,000 - 125,000 per year

Requirements:

• We want someone with 5+ years of software engineering experience, including at least 2 years in applied AI, LLM applications, or production ML engineering.
• We need hands-on experience building LLM-powered solutions on AWS Bedrock, including Knowledge Bases, Agents, Guardrails, and runtime model invocation.
• We need hands-on experience with Snowflake Cortex AI, including Cortex LLM functions, Cortex Search, and Document AI.
• We are looking for strong Python skills, plus familiarity with AI/ML libraries and cloud SDKs such as Boto3, the Snowflake Connector, and orchestration frameworks like LangChain.
• We want experience designing RAG systems, including chunking strategies, embedding model selection, vector store management, and retrieval tuning.
• We expect a solid grasp of prompt engineering, few-shot methods, chain-of-thought reasoning, and structured output techniques.
• We need experience with Snowflake data pipelines and transformations, including efficient SQL, dbt models, and semi-structured data.
• We value familiarity with AI evaluation methods, including eval datasets, retrieval quality measurement, model tracking, and regression management.
• We need experience with AI safety and guardrail practices such as output filtering, PII redaction, moderation, and compliance logging.
• We expect understanding of cloud security fundamentals, including IAM, KMS encryption, and VPC networking in AI deployments.
• We want strong communication skills and the ability to explain AI behavior, limitations, and tradeoffs to non-technical stakeholders.
• A background in financial services, lending, insurance, or fraud detection is a strong advantage.
• Familiarity with additional AWS AI services such as Comprehend, Textract, and SageMaker, as well as Snowflake ML features, is a plus.
• We prefer a Bachelors or Masters degree in Computer Science, Data Science, or a related technical field.

Responsibilities:

• We design and build production AI applications using AWS Bedrock and Snowflake Cortex AI, including RAG pipelines, LLM workflows, agents, and semantic search.
• We integrate foundation models such as Claude, Titan, Llama, and Mistral into our products and internal tools, selecting the best model for each use case based on performance, cost, and compliance.
• We build and maintain AI pipelines with Snowflake native intelligence features, including Cortex LLM functions, Cortex Search, ML classification, and Document AI.
• We develop and support vector stores, embedding pipelines, and document ingestion flows that enable semantic retrieval and context assembly for LLM applications.
• We implement AI agent frameworks and multi-step reasoning workflows using AWS Bedrock Agents, Bedrock Knowledge Bases, and related orchestration patterns.
• We partner with Data Science to bring model outputs, risk scores, and feature signals into LLM context windows so our AI systems can reason over proprietary data.
• We add observability, evaluation, and guardrails to AI systems, monitoring latency, accuracy, hallucination rates, and cost across models and pipelines.
• We manage prompt engineering, version control, and systematic prompt evaluation across use cases and model releases.
• We enforce security, compliance, and data governance across all AI systems, including PII handling, access control, and output logging for financial industry requirements.
• We contribute to AI platform infrastructure, including IAM policies, VPC configurations, Bedrock quotas, and Snowflake role-based access controls.
• We stay current on foundation models, AI tooling, and evaluation techniques, and we bring useful innovations back to the team.

Technologies:

• AI
• AWS
• Backend
• Cloud
• IAM
• Support
• LLM
• Machine Learning
• Python
• SQL
• Security
• Snowflake
• Windows
• dbt
• API
• Claude Code

More:

We are Point Predictive, and we are redefining fraud detection and risk decisioning for lenders through consortium data, machine learning, and real-time systems. This is a hands-on AI Engineer role at the intersection of applied AI, data infrastructure, and product delivery, focused on building the systems that make our risk intelligence smarter, faster, and more actionable for lenders across the financial industry. You will work closely with Data Science, Data Engineering, Product, and backend engineering teams to move AI capabilities from prototype to production in a regulated environment. We offer a competitive salary of $115,000 to $125,000 per year, along with benefits including 401(k), dental, health, vision, life insurance, paid time off, flexible spending account, and health savings account. This is an in-person role based in San Diego, CA, and we are looking for someone comfortable commuting to the office daily.

last updated 32 week of 2026