Key skills
Agentic AI DevelopmentLangChainLangGraphCrewAIAmazon Bedrock AgentsMulti-Agent SystemsLLM IntegrationPrompt EngineeringRetrieval-Augmented Generation (RAG)Function/Tool CallingAnthropic ClaudeAWS BedrockAI Software Development Life Cycle (AI-SDLC)Vector DatabasesPineconepgvectorWeaviateExperiment TrackingMLflowWeights & Biases (W&B)LLMOpsAI SafetyBias DetectionHallucination MitigationJavaJ2EESpring MVCSpring CoreSpring IOCSpringBootSOAP Web ServicesREST Web ServicesXMLJSONAWS API GatewayAWS LambdaAWS SQSAWS ECSAWS DynamoDBAWS S3AWS CloudFormationDockerContainer OrchestrationSQLOraclePostgreSQLAgile MethodologiesTest-Driven Development (TDD)Cross-Timezone Team CollaborationAIMLLLMClaudeAnthropicRAGAgenticMLOpsKafkaSpringTDDIntegration TestingAWSECSCloudFormationLambdaS3DynamoDBSQSBedrockAPI GatewayKinesisSaaSAgileScrumSDLCPrototypingCommunication
About this role
Cortiqa is seeking seasoned Principal Software Engineers to join their Onshore technology office in California. These engineers will serve as technical leads in designing and building Agentic AI-powered integration frameworks, while also owning core application development, system performance, and scalability improvements.
Responsibilities:
- Design and develop Agentic AI systems: autonomous agents, multi-agent orchestration pipelines, and LLM-integrated workflows to accelerate client onboarding and integration automation
- Apply AI-SDLC methodology across the full lifecycle: data strategy, model selection/fine-tuning, agent development, evaluation, deployment, monitoring, and iterative improvement
- Build and optimize client integration frameworks through intelligent automation, leveraging Agentic AI to streamline onboarding and reduce manual effort
- These engineers will be foundational to API's AIDLC transformation, building reusable AI infrastructure, agent frameworks, and tooling that enable product engineering squads to deliver AI-powered features
- Perform software analysis, risk analysis, and reliability analysis for AI and non-AI systems
- Participate in architectural discussions, prototyping, and development estimation for AI-first solutions
- Integrate new software solutions with existing client systems, including airline crew management platforms
- Collaborate in Agile scrum teams; support production issues, functional/system integration testing, and deployment
- Maintain and improve the currency of the IT technology stack, including AI/ML tooling
Requirements:
- Minimum 8 years of experience developing web-based applications; minimum 5 years in Java/J2EE technologies
- Solid full-stack developer with expertise in Spring (MVC, Core, IOC, SpringBoot)
- Strong SOAP/REST web services experience using XML/JSON
- AWS cloud proficiency: API Gateway, Lambda, SQS, ECS, DynamoDB, S3, CloudFormation, Docker/container orchestration, and AWS Bedrock (including Claude model integration, Knowledge Bases, and Agents for Bedrock)
- Strong SQL and RDBMS skills: Oracle, PostgreSQL
- Experience with Agile methodologies and TDD
- Candidates must demonstrate direct, hands-on experience in the following: Agentic AI Development: Design and implementation of autonomous AI agents using frameworks such as LangChain, LangGraph, CrewAI, Amazon Bedrock Agents, or custom orchestration layers
- Multi-Agent Systems: Building multi-agent pipelines with defined roles, memory, tool use, and inter-agent communication
- LLM Integration: Experience with frontier LLM APIs, including prompt engineering, RAG (Retrieval-Augmented Generation), and function/tool calling. Hands-on Anthropic Claude or AWS Bedrock experience preferred
- AI-SDLC: Full lifecycle AI project delivery — from problem framing, data preparation, model evaluation and fine-tuning, through to production deployment and observability
- AI Tooling & MLOps: Familiarity with vector databases (Pinecone, pgvector, Weaviate), experiment tracking (MLflow, W&B), and LLMOps practices
- Responsible AI: Awareness of AI safety, bias detection, hallucination mitigation, and guardrails in production agentic systems
- Comfort with ambiguity and iterative problem-solving in a greenfield AI platform context
- BSc/BA in Computer Science, Engineering, or a relevant field required. Advanced degree or equivalent demonstrated through open-source contributions, research, or AI project portfolio
- Prior airline domain experience, especially crew management or crew services
- Experience delivering AI-powered automation in enterprise SaaS or B2B integration contexts
- Contributions to open-source AI/agent frameworks
- Familiarity with event-driven architectures and streaming pipelines (Kafka, Kinesis) as applied to AI agent triggers