Gen AI Engineer

Tkxel; Lahore; Sur place; PKR 38 770 000 - 49 848 000; Plein temps

Résumé du poste

Tkxel, a leading software development company in Reston, Virginia, seeks a full-stack GenAI engineer to design, build, and iterate AI solutions directly with clients, not just ship code from a backlog.

This role sits at the intersection of backend engineering and applied AI, requiring end-to-end ownership from architecture to handoff and the ability to translate business problems into deployable AI use cases through rapid on-site prototyping.

Qualifications

• Strong GenAI expertise with hands-on experience in LLMs, prompt engineering, RAG, agentic frameworks, and multi-agent design.
• Core stack includes Python, FastAPI or Django, and cloud platforms (Azure or AWS).
• Depth in advanced areas like permission-aware retrieval at scale, async task orchestration, LLM evaluation and observability.
• Business understanding to map client operating models to measurable AI value.

Responsabilités

• Design and build production-grade GenAI systems, including multi-agent architectures and RAG pipelines for enterprise-scale data stores.
• Create agentic systems that reason, retrieve, and act beyond simple chat functionality.
• Collaborate with clients to translate ambiguous problems into deployable AI use cases.
• Prototype rapidly with on-site embedding, shortening the feedback loop from idea to working solution.
• Own end-to-end architecture, implementation, evaluation, and handoff, communicating trade-offs to stakeholders.

Connaissances

GenAI expertise

LLMs

Python

FastAPI/Django

Azure/AWS

Strong communication

Outils

Azure

AWS

Description du poste

Tkxel is a leading softwaredevelopment company located in Reston, Virginia. We are committedto develop innovative software solutions for leading enterprisesin the world, helping them grow their businesses using latesttechnology solutions.

Job Description

We're looking for a full-stack GenAI engineer who can operate directly with client to design, build, and iterate on AI solutions in real time against live business problems, not just ship code from behind a backlog. This role sits at the intersection of backend engineering and applied AI.

Key Responsibilities

Design and build production-grade GenAI systems: multi-agent architectures, RAG pipelines over large/enterprise-scale document stores, and real-time systems used in daily business operations

Build agentic systems that reason, retrieve, and act — not just conversational responders

Work directly with client stakeholders to translate ambiguous business problems into scoped, deployable AI use cases

Rapidly prototype and iterate on-site/embedded with the client, compressing the feedback loop between idea and working solution

Own solutions end-to-end — architecture, implementation, evaluation, and handoff — rather than working purely from fixed specs

Bridge technical and business conversations: explain trade-offs to non-technical stakeholders and translate priorities back into technical decisions

Requirements

Strong GenAI expertise — hands‑on experience with LLMs, prompt engineering, RAG, agentic frameworks, and multi‑agent design; comfortable working across multiple model providers

Core stack: Python, FastAPI/Django, and Azure or AWS

Applied depth in the hard parts, e.g.:

Permission‑aware retrieval at scale

Async task orchestration

LLM evaluation and observability

Business understanding — able to grasp a client's operating model and pressure‑test whether a proposed AI use case creates measurable value, not just technical novelty

Forward‑deployed mindset — thrives working embedded with clients rather than at arm's length; comfortable with ambiguity, direct client exposure, and fast iteration cycles typical of an FDE role

Strong communication skills — able to run discovery sessions, present to leadership, and document decisions clearly.