Location — Rosemond IL (hybrid – 3 days onsite)
We are seeking a high-caliber AI Tech Lead / AI Engineer to design, build, and operationalize agentic AI solutions that accelerate analytics and reporting delivery. This role goes beyond basic agent creation and requires hands-on experience with agent orchestration, memory, and enterprise-grade data access patterns, delivering scalable components that fit into an existing framework while rapidly adapting to incoming business requests.
Responsibilities: –
- Design, Architect, implement, and iterate on agentic AI solutions to shorten the cycle time for analytics, log analysis, and reporting requests.
- Design agent orchestration patterns (multi-agent workflows), tool/function calling, and memory approaches appropriate for enterprise deployments.
- Define secure and scalable data access patterns for agents (retrieval, context building, and grounding), integrating with existing data sources and governance expectations.
- Partner closely with product, analytics, and engineering stakeholders to intake requirements quickly and deliver working prototypes and production-ready solutions.
- Engineer reusable components and best practices that enable scalable delivery (not one-off scripts), aligned to an existing base framework.
- Operationalize solutions for reliability and maintainability: testing strategies, monitoring/observability, prompt/version management, and deployment automation.
- Evaluate build vs. buy options pragmatically when needed, while keeping focus on shipping solutions on the current platform stack.
Tech Stack (Core): –
- Cloud: AWS (primary deployment environment; open to alternatives)
- Data/Analytics Platform: Databricks (including native “chat with data” capabilities and potential agent integrations)
- Agent Frameworks: LangChain, LangGraph
- Conversational analytics patterns: Ask-questions-on-data / conversational BI approaches (agent-driven analytics and dashboards
Experience: –
· 10+ Years
Location: –
· Rosemont, IL (3days/Week)
Educational Qualifications: –
· Engineering Degree – BE/ME/BTech/MTech/BSc/MSc.
· Technical certification in multiple technologies is desirable.
Skills: –
Mandatory skills
- Demonstrated experience delivering agentic AI solutions beyond prototypes, including enterprise deployment considerations.
- Strong hands-on engineering background with AWS-based deployments.
- Experience working with modern data platforms (e.g., Databricks) and integrating LLM solutions with analytics/data ecosystems.
- Ability to operate as a senior individual contributor who can define architecture and implement key pieces end-to-end.
· Excellent communication and collaboration skills with US-based stakeholders
Skills & Expertise Needed
- Agentic AI engineering: building and deploying LLM-powered agents for real business workflows.
- Agent orchestration: designing multi-step and/or multi-agent flows; managing tool use, control flow, retries, and failure handling.
- Agent memory: short-term and long-term memory patterns; conversation state; summarization and context window management.
- Enterprise data access patterns for agents: retrieval/grounding strategies; context assembly from structured and unstructured sources; performance-conscious access.
- Production deployment mindset: security, reliability, monitoring, and maintainability for enterprise-grade AI services.
- Architecture & best practices: ability to design scalable components that fit into an existing framework and can be extended by the team.
- Rapid requirements intake: quickly translating ambiguous reporting/analytics asks into implementable solutions and iterating with stakeholders.
- High autonomy: tech-lead level capability without direct people management; self-directed and able to set engineering direction for the workstream
Good-to-Have Skills
- Experience implementing retrieval-augmented generation (RAG) and hybrid retrieval across structured/unstructured sources.
- Experience with LLMOps practices: prompt/version management, automated evaluation, and regression testing.
- Experience building observability for AI systems (quality metrics, traces, latency/cost monitoring).
- Familiarity with Databricks-specific agent or model serving patterns (where applicable).
· Experience building lightweight analytics experiences on top of agent outputs (e.g., auto-generated insights/dashboards).
We focus on building highly motivated engineering teams and thought leaders with an entrepreneurial mindset, centered on our core values of Passion, Respect, Openness, Unity, and Depth (PROUD) of knowledge. Our success lies in creating a fun, transparent, non-hierarchical, diverse work culture that focuses on continuous learning and work-life balance.
Thanks & Regards,
Prakash Kumar
Appian Infotech Inc
Phone : (205) 990-4911
Email:- Prakash.k@appianinfotech.com
