Senior AI Security Engineer
Abacus Insights10 days ago
Remote, India or Pune, IndiaSenior
Responsibilities
- Partner with AI engineers and technical leads to secure AI initiatives from architecture through production operation.
- Design and build secure AI applications and reusable platform capabilities, including agents, agentic workflows, MCP servers and tools, SQL and RAG agents, retrieval services, and model integrations.
- Contribute production-quality Python, security automation, reference implementations, tests, policy-as-code, and integration components.
- Implement identity, authentication, authorization, least-privilege access, secrets management, tenant isolation, encryption, audit logging, telemetry, privacy, and human approval controls.
- Conduct architecture reviews and threat modeling for prompt injection, excessive agency, insecure tool use, sensitive-data disclosure, retrieval poisoning, dependency risks, and unsafe outputs.
- Build security controls into GitLab CI/CD, code review, testing, deployment, and release workflows, including SAST, SCA, secrets detection, and configuration validation.
- Secure AWS cloud foundations, network connectivity, Terraform infrastructure, knowledge graphs, vector stores, retrieval platforms, MCP gateways, and ingestion pipelines.
- Create secure paved-road templates and coach citizen developers on application registration, data classification, code scanning, secrets management, logging, and production readiness.
- Partner with Privacy, Compliance, and Legal on HIPAA, HITRUST, SOC 2, GovRAMP, ISO 27001, GDPR, BAA, residency, and data-boundary requirements.
- Represent the company in customer-facing security and architecture discussions and provide hands-on support for incidents, design changes, and escalations.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Cybersecurity, or a related field.
- Minimum 5+ years of experience in software engineering, security engineering, platform engineering, DevSecOps, application security, or a related technical discipline, including production systems experience.
- Production experience designing, building, deploying, or securing AI-enabled applications, with hands-on depth in agents or agentic workflows, MCP, RAG, or AI application security.
- Strong Python, API security, testing, code review, automation, deployment, incident response, and configuration management skills.
- Experience securing cloud-native and distributed systems, including identity and access management, authorization, secrets, encryption, network and API controls, logging, monitoring, and secure data flows.
- Hands-on AWS security architecture experience covering multi-account design, service control policies, VPC and Transit Gateway networking, PrivateLink, network firewalls, ECS Fargate, EC2, KMS, Secrets Manager, and CloudWatch.
- Terraform infrastructure-as-code experience, including Checkov policy scanning, OIDC-based CI/CD roles, and repeatable account baselines.
- Experience with graph and vector data stores, preferably Neo4j and Cypher, including vector indexes, fine-grained access control, backup, restore, and data tiers.
- Experience building and securing MCP servers and gateways, including remote authentication, OAuth/OIDC, enterprise SSO, and audit trails.
- Experience designing secure RAG ingestion pipelines, embedding governance, index versioning, secrets and sensitive-data detection, and data classification.
- Knowledge of AI security risks, secure SDLC and DevSecOps practices, SAST, SCA, secrets scanning, threat modeling, risk acceptance, and automated deployment gates.
- Experience reviewing third-party AI services and integrations for OAuth scopes, data flows, vendor security, token lifecycle, retention, and training-use terms.
- Experience in regulated or high-trust environments such as healthcare and familiarity with relevant compliance frameworks.
- Preferred experience includes Databricks, Mosaic AI Gateway, Snowflake, Claude, Azure OpenAI, OpenAI, Gemini, FHIR, Replit Enterprise, Amazon Neptune, Amazon Bedrock, Titan embeddings, Kubernetes, EKS, GitOps, Suricata, and gitleaks.
- Ability to work U.S. Eastern Time hours, with core hours from 9:00 AM to 5:00 PM ET, Monday through Friday.
Benefits
- Competitive leave and benefits.
- Comprehensive health coverage.
- Equity for every employee.
- Growth-focused environment with employee development support.
- Remote role based in Pune, with required alignment to U.S. Eastern Time and a standard schedule of 9 hours per day, 5 days per week.
About Abacus Insights
Abacus Insights builds a cloud-based, AI-ready data platform for health plans that ingests, standardizes, and governs payer and clinical data to power analytics and workflows. Sold as SaaS with pre-built connectors, it supports CMS interoperability, risk adjustment, HEDIS/Stars quality improvement, and payment integrity. Founded in 2017 and headquartered in Boston, the privately held company reports 35 payer customers covering 65 million members.