The Role
Develop and support production-ready AI applications, including LLM features, RAG pipelines, agentic workflows, prompt engineering, tool integrations, and full-stack services. Build secure enterprise connectors, testing and evaluation frameworks, cloud deployments, observability, and operational documentation. Collaborate with architects and stakeholders in Agile delivery while applying secure coding, privacy, responsible AI, and quality controls.
Summary Generated by Built In
Anblicks is seeking an AI Developer to design, build, test, and support AI-enabled applications and integrations. The role combines strong software engineering with practical experience using large language models, retrieval, tool integration, and agentic workflows. The successful candidate will work closely with architects and product stakeholders to convert validated use cases into secure, observable, production-ready capabilities.
Responsibilities
- AI application development: Build LLM-enabled features, RAG pipelines, agentic workflows, intelligent automation, and model/API integrations using clean, modular code.
- Full-stack implementation: Develop backend services, APIs, user-facing components, data integrations, and cloud-native deployment assets as required by the solution.
- Model and prompt engineering: Implement prompt templates, grounding, structured outputs, tool calling, context management, model routing, and evaluation harnesses.
- Integration engineering: Create secure connectors to enterprise APIs, workflow systems, knowledge repositories, data platforms, and approved external services.
- Quality engineering: Develop unit, integration, regression, security, and AI-quality tests, including groundedness, correctness, safety, latency, and cost evaluations.
- Operational readiness: Add logging, tracing, telemetry, exception handling, usage controls, runbooks, and support diagnostics.
- Secure engineering: Follow secure coding, secrets management, least privilege, privacy, data handling, and responsible AI requirements.
- Agile delivery: Estimate work, deliver sprint commitments, participate in design and code reviews, resolve defects, and maintain transparent delivery status.
- Documentation and knowledge transfer: Document code, configuration, interfaces, deployment procedures, architecture decisions, and operational guidance.
Required Qualifications
- 3 to 5+ years of software engineering experience, including at least 1 year building AI/ML or LLM-integrated applications.
- Strong Python development skills or equivalent proficiency in a language used for enterprise AI applications.
- Experience with REST APIs, asynchronous processing, authentication, data access, testing, Git, and CI/CD.
- Practical experience with modern LLM SDKs/APIs, prompt orchestration, RAG, vector retrieval, tool calling, and structured outputs.
- Experience deploying applications on a major cloud platform and troubleshooting across application, model, integration, and data layers.
- Ability to write maintainable, production-ready code and participate actively in peer reviews.
- Comfort working within short iteration cycles and adapting implementation based on evaluation evidence and stakeholder feedback.
- Working knowledge of privacy, secure coding, and responsible AI controls for enterprise applications.
Preferred Qualifications
- Experience with Azure AI Foundry, Azure OpenAI, Anthropic Claude, Model Context Protocol, or comparable AI platforms and frameworks.
- Experience with full-stack frameworks, containers, serverless services, API management, event-driven integration, and observability tools.
- Familiarity with prompt/model evaluation frameworks, synthetic test generation, red-team testing, and LLMOps practices.
- Experience integrating work-management, IT service-management, risk, compliance, or enterprise knowledge platforms.
- Experience in financial services, lending, auto finance, compliance, risk, or another regulated environment.
- Knowledge of SQL, data engineering, semantic layers, vector databases/search, or knowledge graphs.
Skills Required
- 3 to 5+ years of software engineering experience, including at least 1 year building AI/ML or LLM-integrated applications
- Strong Python development skills or equivalent enterprise AI programming proficiency
- Experience with REST APIs, asynchronous processing, authentication, data access, testing, Git, and CI/CD
- Experience with modern LLM SDKs or APIs, prompt orchestration, RAG, vector retrieval, tool calling, and structured outputs
- Experience deploying applications on a major cloud platform and troubleshooting application, model, integration, and data layers
- Ability to write maintainable, production-ready code and participate in peer reviews
- Comfort working within short iteration cycles and adapting implementation based on evaluation evidence and stakeholder feedback
- Working knowledge of privacy, secure coding, and responsible AI controls for enterprise applications
- Experience with Azure AI Foundry, Azure OpenAI, Anthropic Claude, Model Context Protocol, or comparable AI platforms and frameworks
- Experience with full-stack frameworks, containers, serverless services, API management, event-driven integration, and observability tools
- Familiarity with prompt/model evaluation frameworks, synthetic test generation, red-team testing, and LLMOps practices
- Experience integrating work-management, IT service-management, risk, compliance, or enterprise knowledge platforms
- Experience in financial services, lending, auto finance, compliance, risk, or another regulated environment
- Knowledge of SQL, data engineering, semantic layers, vector databases/search, or knowledge graphs
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The Company
What We Do
Anblicks is a Cloud Data Analytics Company based out of Dallas, TX, with offices in USA, India, and Australia. Since 2004, Anblicks has been helping customers by bringing value to their data and implementing modern data architecture and advanced analytics solutions in the cloud.
