Merge pull request 'Senior consultant role update' (#2) from senior-consultant-role-update into main

Reviewed-on: #2

package.json

@@ -17,27 +17,27 @@
     "animejs": "^3.2.2",
     "aos": "^2.3.4",
     "eslint": "8.57.1",
-    "eslint-config-next": "15.5.12",
+    "eslint-config-next": "15.5.28",
-    "next": "^15.5.12",
+    "next": "^15.5.28",
     "react": "^18.3.1",
     "react-dom": "^18.3.1",
-    "react-icons": "^5.5.0",
+    "react-icons": "^5.7.0",
     "react-transition-group": "^4.4.5",
-    "sharp": "^0.34.5",
+    "sharp": "^0.35.5",
     "typescript": "5.9.3"
   },
   "devDependencies": {
-    "@next/eslint-plugin-next": "^15.5.12",
+    "@next/eslint-plugin-next": "^15.5.28",
-    "@types/aos": "^3.0.7",
+    "@types/aos": "^3.0.8",
     "@types/node": "^20.19.33",
     "@types/react": "^18.3.28",
     "@types/react-dom": "^18.3.7",
     "@types/react-transition-group": "^4.4.12",
-    "@typescript-eslint/eslint-plugin": "^8.56.0",
+    "@typescript-eslint/eslint-plugin": "^8.72.0",
-    "@typescript-eslint/parser": "^8.56.0",
+    "@typescript-eslint/parser": "^8.72.0",
     "eslint-plugin-react": "^7.37.5",
     "eslint-plugin-react-hooks": "^5.2.0",
-    "sass": "^1.97.3"
+    "sass": "^1.105.2"
   },
   "engines": {
     "node": ">=18.0.0",
@@ -45,7 +45,11 @@
   },
   "pnpm": {
     "overrides": {
-      "minimatch": ">=10.2.1"
+      "js-yaml": ">=4.3.2",
+      "flatted": ">=3.4.2",
+      "brace-expansion": ">=5.0.12",
+      "minimatch": ">=10.2.3",
+      "postcss": ">=8.5.23"
     }
   }
 }

src/portfolio/data/currentWorkData.ts

@@ -2,23 +2,23 @@ export interface ICurrentWorkData {
 	role: string;
 	company: string;
 	companyUrl: string;
-	specialization: string;
+	specialisation: string;
 	location: string;
 	imagePath: string;
 	paragraphs: string[];
 }
 
 const currentWorkData: ICurrentWorkData = {
-	role: "Technical Consultant",
+	role: "Senior Technical Consultant",
 	company: "Softwire",
 	companyUrl: "https://www.softwire.com/",
-	specialization: "AI Engineering",
+	specialisation: "AI & Data",
 	location: "Manchester, United Kingdom",
 	imagePath: "/portfolio/work_profile.png",
 	paragraphs: [
 		"I spend much of my time <strong>designing and evaluating AI systems</strong>, or systems where AI plays a central role. My work involves the full lifecycle of AI implementation, from initial concept through to production deployment.",
 		"I have <strong>delivered training and adoption materials</strong> that have significantly improved AI usage within Softwire, helping teams understand both the capabilities and limitations of AI technologies. I've also created <strong>autonomous AI pipelines</strong> that have reduced developer burden by automating tasks that were previously time-consuming manual processes.",
-		"Working with <strong>diverse clients</strong> (from the highly skeptical to the enthusiastically optimistic), I've developed expertise in <strong>communicating AI benefits</strong> while respecting organizational constraints. This involves not just technical implementation, but also the human and ethical dimensions of AI adoption.",
+		"Working with <strong>diverse clients</strong> (from the highly sceptical to the enthusiastically optimistic), I've developed expertise in <strong>communicating AI benefits</strong> while respecting organisational constraints. This involves not just technical implementation, but also the human and ethical dimensions of AI adoption.",
 		"A particular area of passion for me is <strong>Ethical AI and Sustainable AI</strong>. I've spent considerable time advocating for sustainability considerations in AI systems, conducting <strong>environmental assessments for embedded AI</strong>, and building adoption systems that leverage <strong>local open-source AI</strong> instead of relying on large providers whose ethical standards can be questionable."
 	]
 };

src/portfolio/data/projectData.ts

@@ -14,11 +14,11 @@ const projectData : IProjectArguments[] = [
 		github: "https://github.com/KuchtaVR6/Multi-LLM-Agent",
 		document: "/multiAgent.pdf",
 		title: "Efficient Agents with Hot-Swappable Adapters",
-		text: "Developed a modular multi-agent system using parameter-efficient fine-tuning to enhance tool use in small language models. Implemented hard routing with expert adapters, achieving performance surpassing larger closed-source models. Demonstrated skills in distributed training, model optimization, and API integration."
+		text: "Developed a modular multi-agent system using parameter-efficient fine-tuning to enhance tool use in small language models. Implemented hard routing with expert adapters, achieving performance surpassing larger closed-source models. Demonstrated skills in distributed training, model optimisation, and API integration."
 	},
 	{
 		imagePath: "latviaEstimation.png",
-		title: "AI Property Valuation with Novel Normalization",
+		title: "AI Property Valuation with Novel Normalisation",
 		tech: [
 			SkillEnum.machineLearning,
 			SkillEnum.research,
@@ -28,7 +28,7 @@ const projectData : IProjectArguments[] = [
 			SkillEnum.computerVision
 		],
 		document: "/DNNpropertyEstimation.pdf",
-		text: "Built a deep learning model combining CNNs and structured data for property valuation, achieving R² of 0.7287. Introduced novel geo-temporal normalization for market dynamics. Applied transfer learning, advanced regularization, and multi-modal data fusion including transport and POI maps. Led data collection and preprocessing."
+		text: "Built a deep learning model combining CNNs and structured data for property valuation, achieving R² of 0.7287. Introduced novel geo-temporal normalisation for market dynamics. Applied transfer learning, advanced regularisation, and multi-modal data fusion including transport and POI maps. Led data collection and preprocessing."
 	},
 	{
 		imagePath: "ipp.png",
@@ -57,7 +57,7 @@ const projectData : IProjectArguments[] = [
 			SkillEnum.python,
 			SkillEnum.numpy
 		],
-		text: "Implemented and analyzed three bio-inspired optimization algorithms: Particle Swarm Optimization, Genetic Algorithms, and Genetic Programming. Conducted comparative performance analysis across different problem domains. Demonstrated algorithm implementation, experimental design, and data analysis skills.",
+		text: "Implemented and analysed three bio-inspired optimisation algorithms: Particle Swarm Optimisation, Genetic Algorithms, and Genetic Programming. Conducted comparative performance analysis across different problem domains. Demonstrated algorithm implementation, experimental design, and data analysis skills.",
 		github: "https://github.com/KuchtaVR6/nat_coursework",
 		document: "/PatrykKuchta_nat.pdf"
 	},
@@ -77,7 +77,7 @@ const projectData : IProjectArguments[] = [
 	{
 		imagePath: "cifar10.png",
 		title: "Deep Learning Image Classification (CIFAR-10)",
-		text: "Built CNN-based image classifier achieving 95.5% accuracy on CIFAR-10 dataset. Applied deep learning techniques including data augmentation, regularization, and hyperparameter tuning. Demonstrated model training, evaluation, and optimization skills. Scored 100% on coursework assignment.",
+		text: "Built CNN-based image classifier achieving 95.5% accuracy on CIFAR-10 dataset. Applied deep learning techniques including data augmentation, regularisation, and hyperparameter tuning. Demonstrated model training, evaluation, and optimisation skills. Scored 100% on coursework assignment.",
 		tech: [
 			SkillEnum.python,
 			SkillEnum.computerVision,

src/portfolio/data/workExperienceData.ts

@@ -1,6 +1,15 @@
 import { WorkExperienceArgs } from "@/src/portfolio/helpers/WorkExperience";
 
 const workExperienceData : WorkExperienceArgs[] = [
+	{
+		industry: "Software & AI",
+		title: "Senior Technical Consultant",
+		company: "Softwire",
+		city: "Manchester",
+		country: "United Kingdom",
+		startDate: "October 2026",
+		isImportant: true
+	},
 	{
 		industry: "Software & AI",
 		title: "Technical Consultant",
@@ -8,6 +17,7 @@ const workExperienceData : WorkExperienceArgs[] = [
 		city: "Manchester",
 		country: "United Kingdom",
 		startDate: "November 2025",
+		endDate: "October 2026",
 		isImportant: true
 	},
 	{
@@ -130,7 +140,8 @@ export const workExperienceParagraph =
 	"I gained experience as a Software Developer Intern at Softwire. During my master's degree, I contributed to " +
 	"the Artificial Intelligence industry as a Programming Data Annotator at DataAnnotation Tech. Upon graduation, " +
 	"I accepted a full-time offer to join Softwire as a Software Developer in their North West office in Manchester. " +
-	"In November 2025, I transitioned to Technical Consultant, AI Specialist. At Softwire, I have gained valuable experience " +
+	"In November 2025, I transitioned to Technical Consultant, AI Specialist, and in October 2026 I was promoted to " +
+	"Senior Technical Consultant within the AI & Data Practice. At Softwire, I have gained valuable experience " +
 	"working on several AI projects, applying my theoretical machine learning knowledge to real-world problems. " +
 	"Across these diverse roles, I have developed a strong work ethic and a broad set of transferable skills.";
 

src/portfolio/sections/CurrentWork.tsx

@@ -9,8 +9,8 @@ const RoleInfo = (): JSX.Element => {
 	return (
 		<div className={styles.roleInfo}>
 			<h3>{currentWorkData.role}</h3>
-			<p className={styles.specialization}>
+			<p className={styles.specialisation}>
-				Specializing in <strong>{currentWorkData.specialization}</strong>
+				Specialising in <strong>{currentWorkData.specialisation}</strong>
 			</p>
 			<p className={styles.company}>
 				at{" "}

src/portfolio/styling/currentWork.module.scss

@@ -172,7 +172,7 @@
 		margin-bottom: 0.3rem;
 	}
 
-	.specialization {
+	.specialisation {
 		font-style: italic;
 		color: #666;
 		margin-bottom: 0.3rem;