This
position
is
listed
on
behalf
of
a
partner
company,
who
manages
all
applications
and
next
steps.
Our
partner
is
looking
for
an
AI
Solutions
Developer
based
in
Canada
.
Join
an
innovative
technology
environment
where
artificial
intelligence,
automation,
and
connected
transportation
converge
to
solve
real-world
business
challenges.
As
an
AI
Solutions
Developer,
you
will
design,
build,
deploy,
and
maintain
intelligent
applications,
AI
agents,
and
automated
workflows
that
improve
business
operations
and
team
productivity.
You
will
develop
production-ready
solutions
using
Python,
large
language
models
(LLMs),
retrieval-augmented
generation
(RAG),
and
modern
cloud
technologies.
Your
work
will
support
sales
enablement,
employee
learning,
customer
education,
and
operational
efficiency
through
secure,
scalable,
and
user-friendly
AI
tools.
Working
closely
with
technical
teams
and
business
specialists,
you
will
transform
complex
requirements
into
practical
applications
with
measurable
business
value.
You
will
also
help
establish
engineering
standards,
implement
responsible
AI
safeguards,
and
optimize
the
performance,
reliability,
and
cost
of
deployed
solutions.
This
remote
opportunity
is
ideal
for
a
hands-on
developer
who
enjoys
experimentation,
continuous
learning,
and
delivering
impactful
AI
solutions
in
a
fast-evolving
industry.
Accountabilities
AI
Application
Development:
Design,
develop,
and
deploy
custom
AI
agents,
intelligent
applications,
and
automated
workflows
using
Python
and
frameworks
such
as
LangChain,
AutoGen,
or
CrewAI.
Backend
Engineering:
Build
and
maintain
backend
services,
microservices,
and
supporting
logic
to
ensure
AI
applications
are
scalable,
reliable,
and
highly
available.
RAG
Systems
and
Knowledge
Integration:
Develop
retrieval-augmented
generation
pipelines
connecting
LLMs
to
proprietary
information
using
PostgreSQL
with
pgvector
and
vector
databases
such
as
Pinecone,
Weaviate,
and
FAISS.
Full-Stack
Development:
Create
end-to-end
AI
applications
with
intuitive
user
interfaces,
robust
backend
functionality,
and
secure
integrations
for
internal
and
external
users.
Workflow
Automation:
Build
self-service
tools
and
intelligent
workflows
that
automate
repetitive
tasks,
streamline
content
creation,
support
localization,
and
improve
training
and
sales
enablement
processes.
API
Development
and
Integration:
Design
secure
RESTful
APIs
and
integrate
AI
solutions
with
business
applications,
learning
platforms,
sales
enablement
systems,
knowledge
repositories,
and
third-party
services.
Conversational
AI
Capabilities:
Implement
conversation
management,
context
retention,
structured
outputs,
and
tool
calling
to
support
interactive
guidance
and
multistep
workflows.
Evaluate
emerging
capabilities
in
speech
recognition,
speech
generation,
interactive
avatars,
and
multilingual
applications.
Cloud
Infrastructure
and
Deployment:
Deploy
and
operate
AI
solutions
using
cloud
services
such
as
Cloud
Vertex
AI,
Cloud
Functions,
Microsoft
Azure,
and
AWS,
aligning
with
established
infrastructure
and
technology
standards.
Security
and
Responsible
AI:
Implement
authentication,
authorization,
role-based
access
controls,
data
privacy
safeguards,
and
protections
against
prompt
injection,
unauthorized
access,
and
unintended
actions.
Maintain
appropriate
separation
of
internal,
partner,
and
customer
information.
Engineering
Excellence:
Establish
and
maintain
CI/CD
pipelines,
automated
testing,
version
control,
code
reviews,
reusable
libraries,
API
wrappers,
and
standardized
development
practices.
AI
Evaluation
and
Performance
Optimization:
Develop
evaluation
frameworks
to
measure
answer
accuracy,
retrieval
quality,
relevance,
and
appropriate
handling
of
unsupported
requests.
Monitor
latency,
token
consumption,
error
rates,
and
operating
costs
to
improve
reliability
and
efficiency.
Maintenance
and
Documentation:
Monitor
deployed
applications,
troubleshoot
issues,
deliver
updates,
and
document
deployment
procedures,
support
requirements,
and
operational
handoffs.
Business
Requirements
and
Solution
Design:
Translate
business
needs
into
detailed
technical
specifications,
assess
feasibility,
define
project
scopes
and
success
criteria,
and
communicate
technical
risks,
dependencies,
and
trade-offs
to
stakeholders.
Cross-Functional
Collaboration:
Partner
with
subject
matter
experts,
IT
teams,
and
AI
platform
specialists
to
validate
technical
solutions,
ensure
content
accuracy,
improve
usability,
and
align
applications
with
business
objectives.
Innovation
and
Continuous
Improvement:
Research
emerging
LLMs,
agentic
frameworks,
and
AI
technologies;
prototype
promising
solutions;
and
identify
opportunities
to
consolidate
applications,
reduce
manual
work,
and
improve
measurable
business
outcomes.
Requirements
Education:
Bachelor's
degree
in
Computer
Science,
Data
Science,
Engineering,
Artificial
Intelligence,
or
a
related
quantitative
discipline.
A
master's
degree
is
an
asset.
Professional
Experience:
Three
to
five
years
of
relevant
experience
in
AI/ML,
data
science,
software
engineering,
or
a
related
field,
with
a
demonstrated
track
record
of
building
and
deploying
intelligent
systems
or
automation
solutions.
Python
Development:
Strong
proficiency
in
Python,
including
experience
with
pandas
and
asynchronous
programming.
Frontend
Development:
Working
knowledge
of
JavaScript
or
TypeScript
for
building
user-facing
applications.
AI
Agents
and
LLMs:
Hands-on
experience
developing
multistep
agentic
workflows
using
code-first
frameworks
such
as
LangChain,
AutoGen,
or
CrewAI,
and
integrating
LLM
APIs
from
providers
such
as
OpenAI,
Gemini,
and
Anthropic.
RAG
and
Vector
Databases:
Practical
experience
designing
RAG
pipelines
and
working
with
PostgreSQL
and
pgvector,
vector
databases
such
as
Pinecone
or
Weaviate,
or
search
libraries
such
as
FAISS.
Cloud
and
Application
Deployment:
Experience
deploying
applications
in
Cloud,
particularly
Vertex
AI
and
Cloud
Functions,
with
familiarity
with
Azure
or
AWS
considered
beneficial.
Software
Engineering
Practices:
Solid
understanding
of
Git,
automated
testing,
CI/CD,
RESTful
API
development,
secure
coding,
and
maintainable
software
architecture.
Data
and
Knowledge
Management:
Ability
to
design
reliable
content
ingestion
and
synchronization
processes
that
keep
connected
knowledge
sources
accurate,
current,
and
appropriately
accessible.
Security
and
Governance:
Understanding
of
authentication,
access
control,
data
privacy,
responsible
AI
practices,
and
the
risks
associated
with
deploying
LLM-powered
applications.
Problem-Solving
Skills:
Ability
to
assess
technical
feasibility,
troubleshoot
complex
issues,
compare
implementation
options,
and
balance
solution
quality
with
development
time
and
operating
costs.
Communication
and
Collaboration:
Strong
written
and
verbal
communication
skills,
with
the
ability
to
explain
technical
concepts,
limitations,
risks,
and
trade-offs
to
nontechnical
stakeholders.
Ownership
and
Adaptability:
A
proactive,
independent
approach
to
taking
solutions
from
initial
concept
through
production
deployment
and
ongoing
maintenance,
along
with
a
willingness
to
learn
and
adapt
to
a
rapidly
evolving
AI
landscape.
Additional
Assets:
Professional
certifications
in
Cloud,
Azure,
AWS,
or
AI
technologies,
as
well
as
experience
with
speech
technologies,
interactive
avatars,
and
multilingual
AI
applications.
Candidates
who
do
not
meet
every
listed
qualification
but
have
relevant
experience
and
a
strong
interest
in
building
practical
AI
solutions
are
encouraged
to
apply.
Benefits
Competitive
Compensation:
Annual
base
salary
ranging
from
CAD
$85,500
to
$105,600
,
depending
on
qualifications,
experience,
skills,
and
work
location.
Flexible
Work
Arrangements:
Remote
work
opportunities,
with
workplace
expectations
and
any
in-person
requirements
discussed
during
the
recruitment
process.
Home
Office
Support:
A
home
office
reimbursement
program
to
support
a
productive
remote
working
environment.
Comprehensive
Healthcare:
Competitive
medical
and
dental
benefits.
Retirement
Savings:
Access
to
a
retirement
savings
program.
Parental
Support:
Baby
bonus
and
parental
leave
top-up
programs.
Professional
Development:
Online
learning
opportunities,
professional
networking,
and
resources
to
support
continued
growth.
Sustainable
Mobility
Incentive:
An
electric
vehicle
purchase
incentive
program.
Innovative
Technology
Environment:
Opportunities
to
work
with
modern
AI
technologies,
cloud
infrastructure,
and
intelligent
automation
solutions.
Collaborative
Culture:
A
diverse
and
inclusive
workplace
that
values
innovation,
teamwork,
continuous
improvement,
and
meaningful
contributions.
Career
Growth:
The
opportunity
to
expand
your
technical
expertise
while
developing
AI
solutions
that
deliver
measurable
business
impact.