XenonStack is the fastest-growing data and AI foundry for agentic systems, enabling people and organizations to gain real-time and intelligent business insights.
Agentic Systems for AI Agents
: akira.ai
Vision AI Platform
: xenonstack.ai
Inference AI Infrastructure for Agentic Systems
: nexastack.ai
THE OPPORTUNITY
-------------------
We are seeking a
Forward Deployed Engineer - Agentic Systems
to work directly with enterprise customers to deploy, customize, and operationalize our AI and agentic infrastructure in mission-critical environments.
This is a
high-impact, customer-embedded role
where you'll act as the bridge between our engineering teams and client operations -- ensuring successful integration, adoption, and measurable ROI from our Agentic AI solutions.
If you thrive at the intersection of
engineering, problem-solving, and customer impact
, and you're excited to bring cutting-edge AI into live enterprise workflows, this role is for you.
RESPONSIBILITIES
--------------------
Deploy & Configure Agentic Systems
Implement AI agents, orchestration layers, and context pipelines tailored to client workflows.
Integrate with Enterprise Data & Tools
Build custom connectors, APIs, and integrations to align with client infrastructure and security requirements.
Optimize Performance & Cost
Tune prompts, context allocation, and model selection for latency, accuracy, and efficiency.
Operational Enablement
Set up observability dashboards, cost tracking, and governance guardrails for client teams.
Customer-Facing Engineering
Work on-site or embedded with client teams to diagnose, resolve, and iterate on solutions in real time.
Feedback Loop to Product
Identify feature gaps, workflow challenges, and optimization opportunities, feeding them directly to our engineering roadmap.
Train & Upskill Client Teams
Deliver enablement sessions on AgentOps practices, multi-agent orchestration, and context engineering best practices.
Prove Value
Track and report adoption metrics, operational improvements, and ROI delivered by deployed systems.
SKILLS & QUALIFICATIONS
----------------------------
Must-Have:
3-5 years in software engineering, AI/ML implementation, or solutions engineering.
Proficiency in
Python
and AI orchestration frameworks (LangChain, LangGraph, AgentBridge).
Experience with
RAG pipelines
, vector databases, and knowledge graph integration.
Familiarity with
cloud deployment
(AWS, Azure, GCP) and containerization (Docker, Kubernetes).
Understanding of LLM architectures, prompt engineering, and context engineering.
Strong client-facing communication skills and ability to operate in high-stakes environments.
Good-to-Have:
Exposure to BFSI, GRC, SOC, or FinOps workflows.
Hands-on experience with observability stacks (Prometheus, OpenTelemetry, Grafana).
Knowledge of AI evaluation tools (TruLens, Ragas, Arize AI).
Familiarity with privacy, compliance, and security standards for enterprise AI.
CAREER GROWTH & BENEFITS
-----------------------------
Continuous Learning & Growth
Training and certifications in multi-agent orchestration, enterprise AI deployment, and observability.
Hands-on exposure to
live enterprise agentic environments
at scale.
Recognition & Rewards
Incentives for successful deployments and measurable client impact.
Fast-track opportunities into
AI Solutions Architecture
or
Client Engineering Leadership
roles.
Work Benefits & Well-Being
Comprehensive medical insurance and project-based allowances.
Cab facilities for women employees and special project perks.