Ab Senior developer python, oracle pl/sql, java Jobs – 117 Openings This Week

AI LLM Technology Architecture
Accenture —Calgary, AB
- $108,800–$220,400 a year
- Full-time
- Engineering
- System design
- Research
Platform Engineer (Software)
BigGeo —Calgary, AB
- Full-time
- Computer Science
- Engineering
- Java
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Senior Water Resources Engineer
Egis Group —Edmonton, AB
- $105,000–$130,000 a year
- Full-time
- Hybrid work
- Civil engineering
- Engineering
- English
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Sr. Software Engineer - Platform Services
ClearGov —Calgary, AB
- $145,000 a year
- Full-time
- Computer Science
- Software troubleshooting
- English
- Designated paid holidays
- Dental care
Quick apply
2d
CCaaS Engineer
Accenture —Calgary, AB
- $69,450–$119,450 a year
- Full-time
- Salesforce
- English
- Java
Senior AWS Lambda (Java) Developer
Play Hockey —Canada
- From $80,000 a year
- Full-time
- Remote
- Computer Science
- Software troubleshooting
- Java
- Disability insurance
- Dental care
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Junior Software Developer
Convverge —Calgary, AB
- Full-time
- Hybrid work
- Azure
- Computer Science
- Databases
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1d
Software Developer
Curve Dental —Alberta
- Full-time
- Remote
- Computer Science
- Software troubleshooting
- Java
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15h
Applied Research Technician IV: Computer Programming (Para sport)
Red Deer Polytechnic —Red Deer, AB
- $29.51 an hour
- Full-time
- Java
- C++
- In-person
1d
Senior Test Engineer, Product Engineering
Chemelex —Edmonton, AB
- Full-time
- Schematics
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- C++
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Junior Developer
Blue Falls Manufacturing —Edmonton, AB
- $55,000–$60,000 a year
- Full-time
- Computer Science
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- English
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- Dental care
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Integration Analyst
Alberta Gaming and Liquor Commission —St. Albert, AB
- $75,282.52–$103,366.67 a year
- Full-time
- Azure
- Computer Science
- Software troubleshooting
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CGI —Calgary, AB
- $60,000–$120,000 a year
- Full-time
- Azure
- Software troubleshooting
- SQL
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AI LLM Technology Architecture

Accenture -
Calgary, AB

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Job details

Full-time
$108,800–$220,400 a year

Qualifications

Cost management
Data integration
Law
Engineering
System design
Research
Enterprise architecture
Bachelor's
Requirements analysis
Deep learning
Mentoring
Natural language processing
AI
Cross-functional collaboration
Software development or architecture experience
System security
Python
Client interaction
Cross-functional communication
Identity & access management

Full job description

You Are:

As an experienced and senior AI/LLM Architect, you will play a pivotal role in designing and delivering end-to-end AI platform architectures that power the modern, reinvented enterprise. Operating at the intersection of business and engineering, you will own the technical design of advanced AI systems — spanning classical machine learning, generative AI, and agentic systems — ensuring they are purposefully architected to meet client business objectives and enterprise-grade standards.

Within this scope, you will take deep ownership of one or more critical architecture domains — such as agentic application design, AI security and trust, AI operations and observability, data and knowledge engineering, or model platforms and inference — serving as the lead authority in your domain across client engagements. You will develop and maintain specialized expertise in the technologies, patterns, and emerging practices within your domain, bringing that depth to bear in shaping architecture decisions, accelerating delivery, and building reusable assets that extend across the practice.

You will evaluate, select, and apply the right design patterns, technical frameworks, and tools within your domain and across the broader AI architecture — ensuring cohesion across the full system. This includes architecting AI agents encompassing multi-agent orchestration, tool use, skills use, and memory systems, as well as the integration of fine-tuned foundation models and classical ML models into scalable, production-ready platforms.

A critical dimension of this role is owning the design of a comprehensive AI context layer — drawing on enterprise knowledge bases, structured and unstructured data sources, and domain-specific content — to ground AI systems in the realities of each client's business and ensure outputs are accurate, trustworthy, and impactful.

As the technical authority on your domains, you will lead architecture decisions and be accountable for ensuring systems meet rigorous non-functional requirements across security, observability, governance, performance, and scalability. You will produce and own the architecture artifacts that shape delivery — including architecture decision records (ADRs), component and data flow diagrams, and integration specifications — and provide the technical leadership that enables cross-functional teams of data engineers, ML engineers, and application developers to execute with clarity and confidence.

Your contributions will be instrumental in shaping how clients adopt and scale AI, pushing the boundaries of what these systems can achieve and delivering measurable, lasting business value.

The Work:

Translate business strategy into a technical vision by defining the non-functional requirements (NFRs) necessary to meet operational goals for performance, reliability, and cost.
Lead stakeholder workshops to align on technical feasibility, define project scope, and manage expectations with clients and leadership.
Drive the technology selection process, evaluating build-vs-buy decisions for AI platforms (e.g., Arize, LangSmith) and foundational models.
Architect model- and tool-agnostic multi-agent systems governed by an MCP Control Plane.
Design and implement the Agent Registry as the mandatory system of record and the AI Gateway for runtime policy enforcement.
Design and implement a certification gate to ensure no uncertified agents enter production, validating identity, policies, and evaluation metrics.
Design, implement, and abstract core agent services, including a first-class abstracted memory service with semantic, episodic, and procedural endpoints.
Architect the end-to-end data pipeline for AI systems, including data ingestion, preprocessing, and synchronization for fine-tuning and RAG.
Design and implement the context layer—spanning knowledge graphs, vector search, and semantic retrieval—to create reliable, grounded RAG pipelines.
Architect foundation model adaptation strategies, including dynamic, cost-and-performance-aware model routing and selection.
Design, implement, and prototype high-throughput, low-latency inferencing solutions using techniques like response caching and request batching.
Define security, governance, and observability as centrally-enforced, by-design controls for all AI systems.
Architect a robust, defense-in-depth security framework, including per-agent identity with IAM/IAP binding and layered guardrails.
Design and implement FinOps controls enforced at the AI Gateway, including token budgets, cost-center labeling, and threshold alerts.
Establish the framework for comprehensive system evaluation, adopting productized tools and instrumenting observability with OTel
Define and maintain the enterprise-wide AI reference architecture, reusable design patterns, and a library of approved software components.
Independently design, implement, build, and deliver proof-of-concept prototypes and foundational software components to validate architectural decisions.
Produce and own authoritative architecture artifacts, including blueprints, sequence diagrams, design specifications, and Architectural Decision Records (ADRs).
Mentor and guide cross-functional engineering teams (data, ML, application) on architectural best practices and design patterns.
Continuously research and integrate emerging AI patterns, frameworks, and technologies to maintain a forward-looking architecture.

Here’s what you need:

Minimum of 5 years of experience in designing & deploying enterprise grade advanced ai solutions using agentic, generative and classical AI/ML using at least one cloud vendor.
Minimum of 2 years of experience in the Agentic, LLM and Generative AI space.
Minimum of 4 years of coding experience using python
Minimum of 2 years of experience architecting and operationalizing LLM driven application architecture patterns.
Minimum of 4 years in coding engineering, machine learning, deep learning and NLP solutions and applications.
Minimum of 4 years of experience as a machine learning architect in the industry designing big data, machine learning. large scale analytical engineering solutions.
Bachelor's Degree or equivalent

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation, based on full-time employment, for roles that may be hired as set forth below.

The recruiting efforts for this position are intended to fill a brand new position.
The base pay range shown below is intended as a guideline to reflect the majority of offers for this role.

It does not represent a maximum limit — in some cases, actual compensation may exceed the range where appropriate.

Information on benefits is here:

Role Location Annual Salary Range

British Columbia/Ontario/New Brunswick $108,800 to $220,400

#LI-NA-FY25 #LI-MP

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senior developer python, oracle pl/sql, java jobs in ab

AI LLM Technology Architecture

Platform Engineer (Software)

Senior Water Resources Engineer

Sr. Software Engineer - Platform Services

CCaaS Engineer

Senior AWS Lambda (Java) Developer

Junior Software Developer

Software Developer

Applied Research Technician IV: Computer Programming (Para sport)

Senior Test Engineer, Product Engineering

Junior Developer

Integration Analyst

Full Stack Developer

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