Artificial Intelligence Engineer

Company Description Teknobit Solutions Inc. is a fast-growing, professionally managed IT talent acquisition company serving clients, implementation partners, and preferred vendors across the USA and India for over 20 years. The organization specializes in rapidly building and scaling sourcing and recruiting teams to meet the hiring demands of large staffing firms and corporations. With deep recruiting industry expertise, Teknobit focuses on delivering high-quality, responsive services tailored to client needs. The company emphasizes transparency and collaboration, positioning itself as a trusted business advisor to its partners. Applicants can expect a dynamic, client-focused environment with opportunities to work on impactful technology initiatives.

● Work as a senior individual contributor within an Agile AI engineering team, partnering with architects, leads, QA, DevOps, data engineers, and client stakeholders.

● Design and build secure Python-based AI services, REST APIs, background workers, integrations, and data-processing components for a production research-assistant platform.

● Build and maintain RAG pipelines across multiple content sources (chat/collaboration platforms, document repositories, and email systems), including ingestion, chunking, metadata extraction, embeddings, indexing, hybrid/semantic retrieval, reranking, and recency-aware ranking.

● Develop and maintain AI agents, tool layers, and MCP (Model Context Protocol) server/client integrations that expose research tools to internal and partner-integrated agents.

● Build conversational delivery surfaces, including a web chat application and a Microsoft Teams bot (channel, personal, and @mention experiences).

● Design and enforce deterministic citation/grounding checks and audit logging so answers remain traceable to real source data, meeting the governance expectations of regulated clients.

● Create prompt templates, structured outputs, validation logic, guardrails, and error-handling mechanisms.

● Write clean, maintainable, testable code; build automated test suites and QA tooling for both conversational agents and MCP servers; participate in peer review and defect resolution.

● Implement logging, telemetry, tracing, dashboards, and operational diagnostics for AI services.

● Lead or significantly contribute to production releases, incident investigation, performance tuning, and continuous improvement, mentoring more junior engineers as needed.

● Follow security, privacy, Responsible AI, coding, documentation, CI/CD, and release-management standards.

● 5+ years of software engineering experience with strong, hands-on Python development; substantial experience building and operating generative AI / agentic solutions in production.

● 3+ years of experience using FastAPI (or a similar framework) to build backend services and REST APIs.

● Hands-on production experience with Azure AI Foundry, Azure OpenAI, and Azure AI Search, or comparable cloud AI/search services.

● Experience with at least one generative AI or agent framework, such as Semantic Kernel, LangChain, LangGraph, LlamaIndex, or a custom tool-calling agent loop.

● Strong understanding of LLM concepts, prompt engineering, tool/function calling, embeddings, hybrid/vector search, RAG, structured outputs, and model limitations.

● Experience with SQL and at least one relational or NoSQL database (PostgreSQL, SQL Server, Cosmos DB, etc.).

● Experience with Microsoft 365/Graph integrations, Microsoft Teams bot development, or Microsoft Fabric/OneLake is a plus.

● Familiarity with MCP (Model Context Protocol) or similar standardized agent tool-calling protocols.

● Comfortable owning a cloud-native service end-to-end: design, build, test, deploy, monitor, and debug production incidents.

● Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field, or equivalent practical experience.

● Strong analytical, problem-solving, and critical-thinking skills; able to operate with minimal supervision.

● Excellent written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders.

● Experience in financial services or another regulated, compliance-sensitive industry is strongly preferred.

● Working knowledge of secure software development, data privacy, Responsible AI, and enterprise governance expectations.

● Python engineering: object-oriented design, asynchronous programming, package management, exception handling, logging, testing, and API development.

● Generative AI development: prompts, conversations, structured output, tool/function calling, content safety, retries, fallback logic, and responsible use of model responses.

● RAG development: document and email processing, chunking, embeddings, vector indexes, metadata filters, semantic and hybrid search, reranking, recency-aware ranking, and source citation.

● Agent development: workflow implementation, tool and API integration, MCP server/client fundamentals, session context, memory patterns, and human-in-the-loop approval checkpoints.

● Data handling: Pandas, NumPy, preprocessing, SQL, JSON, Delta Lake/lakehouse formats, and integration with cloud storage and messaging services.

● Conversational delivery: building chat web applications and Microsoft Teams bots (Bot Framework), including proactive messaging and adaptive card formatting.

● Quality: unit tests, integration tests, API tests, prompt and retrieval evaluation, regression test suites, test data management, debugging, and defect remediation.

● DevOps: GitHub or Azure DevOps, CI/CD pipelines, Docker, Azure Container Apps, environment configuration, secrets management, deployment, and operational monitoring.

● Collaboration and documentation: clear code comments, API documentation, implementation notes, runbooks, demonstrations, and knowledge sharing.

● Ability to work independently and collaboratively with moderate supervision, based on role seniority.

● Ability to work effectively in a hybrid, distributed, and customer-facing environment.

● Ability to travel for business and work beyond normal business hours when necessary.

● Ability to remain flexible and respond successfully to multiple priorities and delivery pressures.

● Ability to sit for extended periods and operate standard computer equipment.