Job Description: Senior Forward Deployed
Engineer (AI/ML)
About the Role
We're seeking a Senior Forward Deployed Engineer who has evolved
from traditional ML engineering into the modern AI stack, bringing a consulting
mindset to customer-facing delivery. You'll embed with clients to design,
build, and ship production AI systems—translating ambiguous business problems
into deployed solutions.
What You'll Do
- Embed
directly with client teams to scope, prototype, and deploy AI-powered
applications end-to-end
- Architect
solutions using modern LLM tooling (agentic frameworks, RAG pipelines,
orchestration layers) while applying rigorous ML fundamentals where they
still matter
- Translate
business requirements into technical roadmaps, then personally build the
systems that deliver them
- Own the
full lifecycle: discovery, POC, production hardening, evaluation, and
handoff
- Serve
as the technical bridge between client stakeholders and internal
product/engineering teams
- Mentor
client and pod engineers on AI-native development practices
What We're Looking For
Core background
- 8+
years hands-on engineering, with demonstrated transition from classical ML
(feature engineering, model training, MLOps) to the modern generative AI
stack
- Prior
consulting or client-facing delivery experience, comfortable with
ambiguity, shifting scope, and stakeholder management
- Strong
software engineering fundamentals (production Python, APIs, cloud
deployment)
Traditional ML foundation
- Experience
building and deploying supervised/unsupervised models, feature pipelines,
and evaluation frameworks
- Understanding
of when classical approaches outperform LLMs (and the judgment to choose
correctly)
Modern AI stack
- Hands-on
experience with LLM application development: prompt engineering, RAG,
agentic workflows, tool use, and function calling
- Familiarity
with orchestration frameworks (LangChain, LlamaIndex, or equivalent),
vector stores, and evaluation/observability tooling
- Experience
shipping LLM systems to production, including latency, cost, and
reliability tradeoffs
Consulting DNA
- Excellent
written and verbal communication; can present to both engineers and
executives
- Self-directed,
able to lead engagements with minimal oversight
- Bias
toward shipping working software over polished slides
What Success Looks Like
Within 6 months, you've independently led at least two client
engagements from discovery to production deployment, established repeatable
delivery patterns, and become a trusted technical advisor to client leadership.
Skills Required
- Strong systems thinking bridging business strategy, operating models, and technical execution.
- Experience building AI-native applications leveraging LLMs, workflow orchestration, and multi-agent systems.
- Hands-on experience with AI engineering tools such as Cursor, Windsurf, Claude Code, and Codex.
- Hands-on experience with agent orchestration frameworks, retrieval architectures, vector databases, LangGraph, LangChain, knowledge graphs, and RAG-based architectures.
- Experience in enterprise transformation, consulting, product operations, platform engineering, or digital transformation environments.
- Strong executive communication, stakeholder management, and cross-functional collaboration skills.
- Ability to operate in rapid sprint-based delivery environments (1-2 week POD cycles) from definition to adoption.
What We Do
Technology, society, economy, policy – all moving at breakneck speed in our 21st century world. You’re feeling the pressure to quickly implement new business models, find new value, make split-second informed decisions and keep one step ahead of customers. How? The answer lies in the ability to make quick, accurate and sustainable business decisions. We believe digital offers a way of doing things better – but the journey to transformation doesn’t have to be painful. At Aligned Automation, we work hard to digitally enable your business strategy – connecting processes, technologies and people to unlock value and drive critical business outcomes.
